Since 80% of the work in a big data project goes toward data integration, it is vitally important to manage big data effectively.
Apache Hadoop technology is transforming the economics and dynamics of big data initiatives by supporting new processes and architectures that can help cut costs, increase revenue and create competitive advantage. An open source software project that enables the distributed processing and storage of large data sets across clusters of commodity servers, Hadoop can scale from a single server to thousands, as demands change. Primary Hadoop components include the Hadoop Distributed File System for storing large files and the Hadoop distributed parallel processing framework (known as MapReduce).
Cloud-baseddata presents a wealth of potential information for organizations seeking to build and maintain competitive advantage in their industries. However, as discussed in “The truth about information governance and the cloud,” most organizations will be challenged to reconcile their legacy on-premises data with new third-party cloud-based data. It is within these “hybrid” environments that people will look for insights to make critical decisions.
Any organisation wishing to process big data from newly identified datasources, needs to first determine the characteristics of the data and then definethe requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, itmay well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs thenclearly new technology will need to be considered to meet the needs of thebusiness going forward.
Data is only as good as the insights it produces, the actions it influences, and the results it fosters. That’s the secret recipe for data management. Your business stakeholders depend on data-based insights to drive decisions and priorities throughout the organization. Insights based on sound data practices can give your business a competitive advantage in the marketplace. Is your data management system ready to support your business?
IBM commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study and examine the potential return on investment (ROI) enterprises may realize by deploying InfoSphere Information Server as part of their overall information architecture integration strategy. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of the InfoSphere Information Server on their organizations.
Every day, torrents of data inundate IT organizations and overwhelm the business managers who must sift through it all to glean insights that help them grow revenues and optimize profits. Yet, after investing hundreds of millions of dollars into new enterprise resource planning (ERP), customer relationship management (CRM), master data management systems (MDM), business intelligence (BI) data warehousing systems or big data environments, many companies are still plagued with disconnected, “dysfunctional” data—a massive, expensive sprawl of disparate silos and unconnected, redundant systems that fail to deliver the desired single view of the business.
Download this white paper for free tips on how to distinguish between different types of business analytics vendors.
Read this whitepaper to learn how Cambridge Semantics has changed the game of data exploration, discovery, analytics and governance for the enterprise.
Data lakes are forming as a response to today’s big data challenges, offering a cost-effective way to maintain and manage immense data resources that hold both current and future potential to the enterprise. However, enterprises need to build these environments with great care and consideration, as these potentially critical business resources could quickly lose their way with loose governance, insecure protocols, and redundant data. Download this special report to understand the key success factors.
The Database Administrator (DBA) job description has historically involved time-consuming tasks such as installation, configuration, and troubleshooting. The arduous on-call nature of the role restricts the capacity of the DBA and, for many companies, has led to high turnover. With the advent of managed services, companies that take advantage of 24x7 support for their DBAs are liberating their DBAs from traditional roles so they have more time to engage in constructive business tasks that take advantage of their most valuable skills – their superpowers.
Robots aren't taking over the world anytime soon – but machine learning has been and will be strengthening security and automating operations for mainframes in the future. As the sheer amount of data housed on mainframes rises, daily operations have become more complex and more difficult to handle manually.
Download this new eBook to learn about the challenges and issues facing mainframes today, and how the benefits of machine learning could help alleviate some of these issues.
A new generation of applications is emerging, spawned in large part by the convergence of big data, mobile computing, social media, and the Cloud. This new generation of applications, also known as “systems of engagement,” connect customers, employees, suppliers, and business partners in real time. The need for speed and enormous scale that characterize systems of engagement has exposed gaps in legacy database technologies that pose significant challenges for deployment teams tasked with ensuring that all system components integrate efficiently and reliably. Download this white paper to learn how to modernize your enterprise database architecture.
MongoDB is the leading NoSQL software. It is open-source and supported by a strong community of users. It can be used unsupported, in the community version, or supported with the enterprise edition. But it is important to keep your version updated with the latest upgrade. As of 2017, it also comes in a hosted version called Atlas, which provides both storage and software in the cloud. MongoDB can be used with a variety of storage solutions — on premises, in the cloud, or hybrid.
What if your DBA announced his or her retirement tomorrow? Or, worse, just quit on the spot? What would you do? In this white paper, we will take a deep dive into DBA supply and demand realities and what they mean for organizations across the board, issues surrounding DBA training and industry burnout, and what today’s companies can do to avoid creating a situation where DBAs become a Single Point of Failure for database management and maintenance.
One of the biggest changes facing organizations making purchasing and deployment decisions about analytic databases — including relational data warehouses — is whether to opt for a cloud solution. A couple of years ago, only a few organizations selected such cloud analytic databases. Today, according to a 2016 IDC survey, 56% of large and midsize organizations in the United States have at least one data warehouse or mart deploying in the cloud.
Take a closer look at how three companies capitalized on more data—almost instantly—with IBM® BigInsights® on Cloud.
So, how do you ensure availability? How do you know your complex car or your complex computing system is running smoothly? How do you tell when a small, yet critical component is failing, and disaster is just around the corner? Download this white paper to learn the answer!
Contrary to industry lore, the mainframe is not “inherently” secure. While it is generally more secure than its distributed counterparts, stricter security measures are nevertheless required for today’s compliance needs — not to mention peace of mind.
There are a number of different data sources that are available within the IBM z/OS mainframe that can be leveraged to provide insight into the operational health of the system and applications as well as visibility into security and compliance issues. This new white paper discusses emerging technologies, Splunk and Ironstream, that enable organizations to capture mainframe information and quickly move it to open-system platforms where it can be integrated and correlated with information from other platforms, analyzed for anomalies and issues, and visualized using a platform that is familiar and comfortable for today’s workforce.
When it comes to extracting actionable knowledge from data, there are two really important variables: the amount of data analyzed, and the speed of analysis. The amount of data available for analysis is piling up at a phenomenal rate, causing problems with finding room and time to analyze that data without hurting operations. Turning this data deluge into an asset has become a key priority for IT executives. Data analysis used to be done with backups of the database in off-peak hours. But in today's demanding IT environment, there isn't really an off-peak moment, and data gets stale fast. Accurate analysis requires fresh data. In many operations, two-minute-old data is expected, two-hour-old data is suspect, and two-day-old data is useless. A major solution to issues of space and latency is Oracle GoldenGate — a program designed for the easy and fast replication and migration of data from many sources to many sources.
While every company has its own specific set of requirements for the NoSQL database technology that best fits its use case(s), there’s a core set of requirements that figure into most evaluations. Those requirements fall into eight categories: Data Access, Performance, Scalability, Availability, Multiple Data Centers, Big Data Integration, Administration, and Mobile. This paper delves deeply into each core requirement and provides a comparison of leading NoSQL databases against the eight core requirements.
Today’s web, mobile, and IoT applications need to operate at increasingly demanding scale and performance levels to handle thousands to millions of users. Terabytes or petabytes of data. Submillisecond response times. Multiple device types. Global reach. Caching frequently used data in memory can dramatically improve application response times, typically by orders of magnitude.
Today’s consumers rely on their mobile apps no matter where they are. If your apps are sluggish and slow or don’t work at all when there’s no internet connection, your customers will start looking for other apps that work all the time. To help you provide the always-on experience customers demand, database solutions like Couchbase Mobile have added synchronization and offline capabilities to their mobile database offerings.
Couchbase has been named a leader in “The Forrester Wave™: Big Data NoSQL, Q3 2016,” by enabling enterprises to successfully compete in the Digital Economy across industries including eCommerce, streaming media, gaming, finance, healthcare, and more.
The report examined 26 criteria to evaluate the current offering, strategy, and market presence of 15 Big Data NoSQL solutions. It cited scalability, flexibility, performance, simplicity, and cost as the primary reasons to embrace NoSQL.
Couchbase was recognized for “ease of use” and the report noted that Couchbase customers use it “to support various mission-critical workloads, including operational, analytical, and mixed workloads.” Couchbase also received high scores for development, deployment, and support.
More and more businesses are deploying embedded BI solutions as a value-added offering to their customers. Learn how ISCS, Urban Airship, and Campus Logic are using Powered by Looker to rapidly implement the right analytics solution for their customers while managing costs and staying focused on their core business priorities.
Despite its promise to liberate users from reliance on the IT department, self-service analytics is not easy to achieve. Many companies that have deployed self-service analytics have become inundated by a tsunami of conflicting reports, spreadmarts, renegade reporting systems, and other data silos. These companies have learned that the goal of self-service is not unfettered liberation from IT, but rather a partnership that balances freedom and control, flexibility and standards, governance and self service.
For developers, data scientists and IT decision-marketers.
This report is designed to help you make an informed decision about IBM Cloudant. It is based on 43 ratings and reviews of Cloudant on TrustRadius, the trusted user review site for business software.
There are many types of databases and data analysis tools to choose from when building your application. Should you use a relational database? How about a key-value store? Maybe a document database? Is a graph database the right? What about polyglot persistence and the need for advanced analytics?
In a multi-database world, startups and enterprises are embracing a wide variety of tools to build sophisticated and scalable applications. IBM Compose Enterprise delivers a fully managed cloud data platform so you can run MongoDB, Redis, Elasticsearch, PostgreSQL, RethinkDB, RabbitMQ and etcd in dedicated data clusters.
Database administrators are still in demand despite the shift to the cloud, the advent of DevOps, and the automation of many IT tasks. In fact, DBAs are becoming more critical to IT departments: their technical background and expertise in data storage and integration means they are in the ideal position to take on strategic and advisory roles with regards to the tasks that have now been taken on by technology. In this white paper, we explore how the DBA role has changed, and how DBAs now play an equally critical but more management-oriented role in IT departments.
Today, more than ever, businesses rely on IT to deliver a competitive edge. They want efficiency, agility and the ability to innovate through better collaboration, visibility and performance. However, as data sources, workloads and applications continue to grow in complexity, so does the challenge of supporting them. To be successful, businesses need faster, more flexible and more scalable data management processes. Answering this call is a new generation of hybrid databases, data architectures and infrastructure strategies. Download this special report for an overview of the key technologies and strategies in the fast-growing world of hybrid data management.
Organizations can no longer afford to rely on a traditional data warehouse solution to support new business intelligence (BI) requirements along with their existing BI workloads. The rigid development, operation, and management process that characterizes traditional solutions is insufficient to support new BI requirements such as fast and agile report development, investigative analytics, data science and self-service BI.
5 Reasons Why You Need SharePlex for Migrations and High Availability
Think you need Oracle GoldenGate, Streams or DataGuard? The truth may surprise you! Get this tech brief to discover the affordable golden alternative trusted by some of the most successful companies in the world. You’ll see how it delivers more functionality – at a fraction of the cost.
IBM DB2 tricks and tips!
Want to spend less time managing DB2 and more time innovating? Check out this tech brief to learn expert techniques that’ll save you hours. You’ll see how Toad can help you automate tasks, ensure peak database performance and much more.
See how to break down silos between development and operations teams, so you can enter the DevOps fold. In this white paper, you’ll learn how to use automation to enable agile database development.
What’s the secret to producing high-quality applications under tight deadlines? Automation. Learn how to use it to your advantage in this eye-opening e-book. You’ll see how to eliminate stress and become part of a high-functioning development team.
It’s time to make proactive database management and productivity a reality with Toad. Read the tech brief.
When you say “migrations and upgrades” to a database or systems administrator, what they often hear is “risk and downtime.” It doesn’t have to be that way. Find out how you can simplify the migration and upgrade process to minimize risks and avoid getting stuck in the office after hours.
Is it possible to retrieve data needed for making business-critical decisions from your production database without affecting performance or productivity? Hardware upgrades or maintaining several databases for reporting and analytics can help, but it also drives up costs. See how Shareplex can provide a solution that’s both easy and affordable.
For years, the ability to analyze data to discover new insights through impressive visualizations and rapid prototyping with custom, ad hoc, or enterprise data has been desired by Oracle customers. Now, as part of the Oracle Business Intelligence Enterprise Edition (OBIEE) system and Business Intelligence Cloud Services (BICS), Oracle Business Intelligence Visual Analyzer technology has filled the gap with an integrated solution that gives business users and developers alike the power to gain insights. Additional options through Big Data Discovery (BDD) and Data Visualization Desktop (DVD) now empower users at all levels of the organization unlike ever before.
In this white paper, we will discuss how straightforward it is to tell a compelling story with data and prototype with greater speed while gaining insights into information with this new cutting-edge data visualization access.
When you’re ready to virtualize or Cloud-enable your database, Tibero is the logical choice to drive your digital business. Agile companies–from small to enterprise–choose Tibero for its performance, scalability, out-of-the-box security, and flexible licensing.Tibero’s licensing model allows enterprises to fully maximize their virtualization investment by only licensing the cores associated to a given VM, rather than Oracle’s soft partition model of licensing 100% of the cores, regardless of how much of the resources the database consumes.
If you are currently relying on Oracle Standard Edition (SE) or Standard Edition One (SE1) to underpin your applications, migrating to SE2 will mean that the cost and complexity of maintaining those applications is likely to increase significantly. Our customers describe a ‘migration’ to Tibero as being no more risky and requiring no more development and testing effort than would be required for a major Oracle version update.
Imagine calling your local carpet cleaning company to get a quote for your home. Now imagine being quoted a price not based upon the number of rooms with carpet, but rather how many total rooms in your house or how many people live in the house, or if you’re willing to build a moat between the family room and kitchen. That’s the reality corporations are dealing with today when attempting to purchase enterprise applications, including databases. More often they’re asked for named users, core count or the type of “trusted” partition they are planning on using, rather than how much of the service they will actually use.
In partnership with TmaxSoft, fonePaisa has built a dynamic, yet secure database infrastructure with Tibero, which supports the needs of their business today, and one that will expand to meet the future demands of their digital business – with a 64% lower total cost of ownership (TCO), and at one-third the cost of Oracle.
Storyboarding is a great way to kick-start a report or a development project. It allows the creator to put ideas into a tangible format that can be revised as necessary. It also helps create a feel for how the reporting will look once the reports are built.
There are various ways of integrating storyboarding into the requirements-gathering process, particularly within the Oracle Analytics product suite. This white paper reviews several methods for creating storyboards in the requirements-gathering process and discusses how these methods can be specifically applied to Oracle analytics dashboards and reports.
For data managers and administrators, IoT presents new types of challenges to their jobs. The rising tide of data - in all its various forms - has been a challenge for some time now. Data managers have been responding with more hardware, more database tuning, more storage, and more cloud. But data keeps growing, and with the rise of IoT, it will grow geometrically. Download this special report for the key considerations you need to make as you begin your IoT journey.
There's no such thing as a self-driving database. If you expect your Oracle databases to perform consistently at high levels, you need to have a maintenance program. The first part of that program is an assessment: How is my database performing, and are there any problems? It sounds simple, but for most modern complex database environments, a proper assessment requires a variety of tools and a lot of experience interpreting the results. This white paper takes readers step-by-step through an Oracle database health check. We'll look at issues related to size, space, configuration, performance, security, and best practices. We’ll also see why in many cases it's prudent to bring in an independent third party to perform your database assessments.
In this whitepaper, we discuss the new features and product functionality in EBS 12.2, problems experienced with the EBS 12.2 upgrade, and Datavail's proven upgrade approach methods with minimal downtime. Oracle EBS 12.2 has led to greater efficiency and high flexibility with the new centralized and standardized key business functions that have improved support for shared services as well as standardized and simplified financial infrastructure across enterprises.
This report describes the 10 most salient features of a modern analytics platform. The list is not
exhaustive, but it provides business and Bl managers a good sense of what to look for in a new or existing Bl
and analytics product. It is designed to jump-start discussions with prospective vendors about their product
road maps and capabilities.
A successful sales team is at the heart of every successful organization, with every salesperson responsible for driving revenue, bringing in new business, and nurturing existing customer relationships. Today, organizations have an unprecedented opportunity—a chance to arm their sales reps with timely, relevant customer information. Access to this information gives salespeople the ability to research prospects’ interests, personalize outreach, identify new opportunities, and get the information they need to answer tough questions during face-to-face interactions.
This White Paper introduces the Vblock 540, a revolutionary new platform for modernizing deployment and management of mixed-workload and mixed-application environments such as Oracle, Microsoft, and SAP. Using all-flash XtremIO storage, the Vblock 540 offers a fast, cost effective path that scales with the growth of your business demands making it the ideal platform for mission critical applications.
This White Paper shows how the new Vblock 740 is an engineered solution that enables simplified management of mixed- application workloads such as Oracle, Microsoft and SAP. With fewer complexities, consistent performance and protection across all their applications, DBAs and Application teams can focus more on innovation and driving more value to the business.
This solution guide describes a Dell EMC Vblock® System 540 converged infrastructure solution that highlights flexible scaling options and tight integration with Splunk Enterprise for analyzing large quantities of machine data.
Underpinning the movement to compete on analytics, a major shift is taking place on the architectural level where
data is captured, stored and processed. This transformation is being driven by the need for more agile data management
processes in the face of increasing volumes and varieties of data, and the growing challenge of delivering data where
and when it is needed. Right now, data architecture is more important than ever, and one thing is clear: the old models
aren’t enough for today’s data-driven business demands.
This white paper covers the use case of a public sector organization in detail to provide an overview of how an Oracle Business Intelligence system can be built, organized, and fine-tuned to provide a solid anchor from which more profitable analytical insights and business decisions can be extracted.
Where once the data center (DC) was hidden away within the domain of IT, the age of the customer entreats all to come forward and partner together for business success. If organizations want to become nimble, customer-centric leaders (and they most certainly do), they must modernize to keep up with increasingly complex data needs in real time. As such, the modernized data center must function in service of the business, the board room, and the bottom line if it is to remain not just relevant but also innovative.
As the paradigm of business changes and adapts to new technologies and strategies, the role of DBAs must adjust too. Today it is called DevOps, the combination of working relationships between Development and Operations. While the typical definition and implementation of a DevOps environment does not outline a specific role for the DBA to play, this change in form and function throughout IT will require DBAs to completely rewire their thinking when it comes to their position. Task-oriented approaches will need to become more strategic; independent duties will necessarily need to become more collaborative.
During this product launch live webinar, Dion Picco and Sumit Sarkar introduced the Progress DataDirect Hybrid Data Pipeline and delved into use cases where this industry-first, embeddable hybrid data access service overcomes several key obstacles, including accessing on-premises data behind the firewall. Watch the demo and see the future of hybrid connectivity.
In 2014, Intuit’s Jerry Lekhter faced a user experience roadblock: data needed in the Salesforce portal was stuck in legacy CRM systems. How do they give their employees access to more data inside of Salesforce to serve their customers better? And how do they do it without getting bogged down in legacy integration, searching for customer data? Find out how they did it.
In this tutorial, Progress DataDirect introduces the Hybrid Data Pipeline, the industry’s first embeddable hybrid data access service. Now, you can host the DataDirect Cloud solution on Azure or any other cloud. Find out how fast and easy it is to access all of your data, even data behind the firewall.
This whitepaper focuses on the reduction of EBS storage footprint. We start by clarifying the reasons for the rapid growth of data and subsequent rapid rise in storage, explain how this affects business and profits, and illustrate the benefits of reducing EBS storage footprint. We continue by discussing the importance of utilizing the two solutions, Delphix and XtremIO, for reducing EBS storage footprint. Finally, we show how XtremIO works in conjunction with Delphix.
Let us help you uncover your potential.
Tell us about your organization and learn where you could be cutting costs and making improvements with the SAP HANA Cloud Platform.
Introducing a complete, agile, and open cloud platform like no other.
The SAP HANA Cloud Platform is an in-memory cloud platform that lets you rapidly build, deploy, and manage cloud-based enterprise applications that complement and extend your SAP or non-SAP solutions. As the only cloud platform built on the SAP HANA platform, it powers the real-time applications companies need to succeed in today’s world. With it, mobile-ready web and portal applications can bring together business and social content, with minimal IT involvement and disruption to existing systems.
This report focuses on the seven core technologies currently driving digital transformation today. They are: Big Data, Cloud Computing, Cognitive Computing (Artificial Intelligence), Mobility, the Internet of Things (IoT), Virtualization, and 3D Printing. This report provides qualitative and quantitative insight into each technology, their rate of adoption, their value to business ecosystems, and their present and future capabilities.
This white paper reports on the experience of businesses, large and small, in a variety of industries, in moving their databases to Amazon Web Services (AWS). We will begin by exploring the differences between Amazon Relational Database Services (RDS) and Amazon Elastic Compute Cloud (EC2). Then we'll follow Datavail DBAs as they assist a variety of clients with assessment to migration, configuration, replication, monitoring, and tuning. Each of these processes is illustrated with an actual case history drawn from customer service evaluations. If you are considering moving databases to AWS, we think you'll find this Datavail white paper to be a helpful guide to the process of migrating your database environment to the cloud.
How do the latest releases of two leading NoSQL databases compare on both read/write and query performance? The emerging technologies thought leader Avalon Consulting, LLC benchmarked MongoDB 3.2 and Couchbase Server 4.5 to find out. These big data experts ran industry standard (YCSB) workloads for both read/write and query.
The bottom line: Couchbase outperformed MongoDB by 7x on reads, 5x on writes, and 3x on queries.
Data modeling is the exploration of the structuring of your data. The exercise involves understanding both the application requirements and the underlying database platform. Application logic informs the entities and relationships. The database platform provides the tools to represent the logical entities in the physical world with methods to store and retrieve instances of the entities.
In today’s digital economy, leading companies like Best Buy Canada, Nike, Staples, and Walmart are turning to NoSQL databases for better performance, availability, flexibility, and agility at lower cost – while providing customers with the amazing user experience they demand. In the white paper, “Why retail and eCommerce are making the move to NoSQL,” you’ll learn:
-The top eCommerce use cases for NoSQL
-How NoSQL is uniquely able to meet the key requirements of a scalable, agile database
-What kind of data can be stored in a NoSQL database, how it’s modeled, and what it looks like
While the hype surrounding NoSQL database technology has become deafening, there is real substance beneath the often exaggerated claims. But like most things in life, the benefits come at a cost. Developers accustomed to data modeling and application development against relational database technology will need to approach things differently. This white paper highlights the differences between a relational database and a distributed document-oriented database, the implications for application development, and guidance that can ease the transition from relational to NoSQL database technology.
MongoDB 3.0 includes WiredTiger, an optional storage engine, to address performance issues. It’s better than the default storage engine, but how well does it improve MongoDB performance? Avalon Consulting, LLC, big data experts and thought leaders in emerging technologies, benchmarked MongoDB 3.0 with WiredTiger and Couchbase Server 3.0.2 to find out. The bottom line: Couchbase outperformed MongoDB by a factor ranging from 2x to 4.5x.
This white paper highlights the differences between a relational database and a distributed document-oriented database, the implications for application development, and guidance that can ease the transition from relational to NoSQL database technology.
Many digital transformation adherents believe a key benefit can be the delivery of more personalized customer experiences, but actually achieving this goal has been fraught with challenges. Companies still struggle to gain a full understanding of the interests, desires, and needs of their customers as individuals. And even loyal customers may feel that they’re all but anonymous to the companies they’ve long supported.
Today’s sales environment is the most competitive it has ever been. More than ever, companies need to leverage technology to optimize operations, maximize performance, and provide powerful sales enablement tools that help teams sell more efficiently. Despite this, nearly 50% of sales time is still wasted on unproductive prospecting. This is because most sales systems (SFA/CRM) fail to enable sales processes out of the office and do not provide enough insight into customers. These systems provide basic operational reports and charts but only provide sales teams with 10% of what is needed to be successful.
The healthcare industry is undergoing tremendous change driven by regulatory reforms, technological advances, and the explosive growth of data. Initiatives such as the Affordable Care Act are shifting the industry’s focus toward value-based healthcare, giving consumers more options for how they receive and pay for their health services while exposing providers to new levels of accountability and competitive pressure. In this new model, healthcare organizations must be more attentive to the cost and quality of care delivery, and they must be more willing to leverage new technologies to deliver more cost-efficient and convenient care to patients.
This is an era of unprecedented economic, regulatory, and technological challenges in the banking industry. Economic conditions are volatile and low interest rates have impacted profitability. Regulatory requirements continue to increase in scope and complexity and heavily influence bank operating costs associated with compliance. The explosive growth of mobile devices has helped to make financial information and investment tools readily available to consumers, and the competition is capitalizing on new technologies.
A picture is worth a thousand words. But in the case of dashboards, pictures can quickly translate into thousands of dollars. Information is arguably better absorbed through vivid visualizations as opposed to monotonous grids, as visualizations can address the scope and dimensions of underlying data in a succinct and digestible format.
The globalization of manufacturing puts immense downward pressure on production costs. Manufacturing companies face the challenge of generating productivity improvements in areas that are already relatively efficient. Additionally, providing after-sales services(installation, maintenance, repairs, extended warranties, or replacement parts) means that companies have even more systems to manage with an ever-growing pool of information to analyze. Concurrently, customers are better informed on product performance and pricing, heightening their expectations and demands.
This eBook explains how databases that incorporate semantic technology make it possible to solve big data challenges that traditional databases aren’t equipped to solve. Semantics is a way to model data that focuses on relationships, adding contextual meaning around the data so it can be better understood, searched, and shared. Discover the 5 steps to getting smart about semantics and learn how leading organizations are integrating disparate heterogeneous data faster and easier with semantics.
This quick, concise eBook provides an overview of NoSQL technology, when you should consider using a NoSQL database over a relational one (and when to use both). Additionally, this book introduces Enterprise NoSQL and shows how it differs from other NoSQL systems. You’ll also learn the NoSQL lingo, which customers are already using it and why, and tips to find the right NoSQL database for you.
This paper will provide insights and guidelines to help you learn how to leverage all of your data to reach your data integration objectives with less time and expense. The key is to start with the end in mind by undertaking your next data project armed with the right technology to succeed. In this paper, we’ll give you real-world examples of organizations that embraced change and found success.
In this white paper, we dive into the details of why relational databases are ill-suited to handle the massive volumes of disparate, varied, and changing data that organizations have in their data centers. It is for this reason that leading organizations see dramatic results when they are going beyond relational to embrace new kinds of databases.
In this white paper, we investigate the SQL Server database backup options in Azure Virtual Machine. We start by explaining the uses and importance of backing up databases. We continue by discussing the Azure Virtual Machine (VM) concept, the services offered by Azure, the kind of Azure Storage architecture, storage types, and the recommended storage management tools. Finally, we examine the backup options of SQL server on Azure VM and outline the best practices of setting up SQL server database backup on Azure VM.
This paper describes why BITeamwork is important to organizations with a Business Intelligence tool, specifically Oracle BI (OBIEE). It identifies various industry-specific and cross-enterprise processes that can be positively affected by BITeamwork Collaborative BI. The paper also identifies the benefit drivers of Collaborative BI and calculates the costs and Return on Investment (ROI) gained from a BITeamwork implementation. We introduce the framework, functionality highlights, API, and help the reader create their own business case for collaborative BI with BITeamwork.
In this whitepaper, we discuss extending WebLogic domain. We start by illustrating the components of WebLogic domain infrastructure and discussing the constraints and recommendations to follow when setting the WebLogic domain infrastructure. We continue by explaining the concept of WebLogic domain extension process and the steps of extending the WebLogic domain. Finally, we examine the limitations of extending WebLogic domain and delve into the solutions and benefits of this process.
This whitepaper illustrates the SQL Server 2016 business intelligence/data warehouse upgrades, the memory-optimized tables, and the columnstore indexes. We also discuss the performance comparison of in-memory tables and columnstore indexes and outline how to do a performance comparison with Azure. Finally, we conclude by examining the performance comparison caveats.
Beginning, expanding, or refining a BI analytics solution is a complex endeavor for any company. From building or configuring a data warehouse, to installing new software or applications, to building relevant reports and dashboards, it’s often more time-consuming and costly to implement these structures using existing resources that are already tied up in other important strategic initiatives. Down this special white paper to learn the seven BI and Analytics services that strengthen your Oracle infrastructure.
Today, you can’t pick up a magazine, read a blog, or hear a webcast without the mention of Big Data. It has had a profound effect on our traditional analytical architectures, our data management functions, and of course, the analytical outputs. This paper describes an analytical architecture that expands on the existing Enterprise Data Warehouse (EDW) to include new data sources, storage mechanisms, and data handling techniques needed to support both conventional sources of data and those supplying Big Data.
In this paper, we propose a guide for comparing the ERwin 9.64 and ER/Studio 2016 modeling tools. The comparison covers only a limited set of key features that relate to key differences between the two modeling tools. Many features that are more or less similar are excluded in this document.
Metadata may not be the sexiest topic, nor may it be at the forefront of everyone’s mind. But it needs to be. The operational culture of the enterprise has gradually shifted towards a more business-centric model, one where business users and front line information consumers do not just desire better access to enterprise data assets, but need to have a comprehensive view of the organization. This means that data, as well as the metadata that describes it, must be shared, both at the developer level and the BI level. This is easier said than done.
Maintaining the performance and availability of business-critical systems and applications is stretching most IT departments to the limit. To address this challenge, many are currently evaluating new technologies and strategies, including database monitoring tools, new types of databases, and virtualization and cloud approaches. Download this special report to learn about the key solutions available today.
The goal of any business is to get the most out of every investment. One of the more critical investments is database performance. Access this infographic to see how to address several common business and technology challenges effecting your database's performance and how to solve them.
Clearing technological obstacles, improving productivity and maximizing your infrastructure’s flexibility are the differentiators that will help your business achieve greater performance and flawless resilience, all with a lower total cost of ownership (TCO).
Access this white paper to learn how to resolve issues with
- Underutilized CPUs
- Database configuration issues
- Legacy storage and compute systems
Understand these issues and how they are driving up your TCO.
Businesses worldwide rely on their databases to support enterprise applications, and have accordingly invested heavily in getting the best possible operational results. Yet deploying, tuning, and troubleshooting databases isn’t always easily, obviously, or quickly achieved.
Download this whitepaper to learn about the solution Hitachi Data Systems is deploying to tackle these problems with
- Troubleshooting and diagnostic capabilities
- Growth trends and size estimates
- And much more
Data growth demands and the requirement for real-time analytics and ongoing cost reductions create a challenging environment for IT leaders and their teams. To respond to growing demand from customers and internal users, mission-critical apps must always.
The growth in enterprise applications continues to put pressure on Oracle DBAs and infrastructure teams to optimize speed, availability, agility and cost reduction all atonce.
Access this white paper to learn how to solve the top 3 DBA Challenges around
- Limited Agility
- Continuous availability
- Resource Constraints
Read Forrester's Total Economic Impact™ (TEI) study and see why Hitachi Unified Compute Platform (UCP) was the best of five platforms examined, and the potential return on investment (ROI) enterprises may realize by deploying Hitachi Unified Compute Platform for Oracle Database.
As organizations look to become more digital, data movement, management, and governance are in the crosshairs for improving analytics and business outcomes. Advances in management technology have helped big data come out of the shadows and solidly into business operations. More recently, advancements in real-time data movement technology have cut down on the latency and time to value of data analytics.
Marking its 10th anniversary this year, Hadoop has evolved from a platform for batch processing large data sets to a robust ecosystem of next-generation technologies aimed at solving a myriad of real-world big data challenges today. From NoSQL databases, to open source projects like Spark, Hive, Drill, Kafka, Arrow and Storm, to commercial products offered on-premises and in the cloud, the future of big data is being driven by innovative new approaches across the data management lifecycle. The most pressing areas include real-time data processing, interactive analysis, data integration, data governance and security. Download this report for a better understanding of the current landscape, emerging best practices and real-world successes.
Ponemon Institute is pleased to present the findings of Big Data Cybersecurity Analytics, sponsored by Cloudera. The purpose of this study is to understand the current state of cybersecurity big data analytics and how Apache Hadoop based cybersecurity applications intersect with cybersecurity big data analytics.
This paper proposes a different perspective on big data and asserts that it’s not the “what” of data but, rather, the “how” that really matters. It also argues that if you don’t have a well-thought strategy, you’re not going to get very far and will find yourself at a competitive disadvantage.
We live in a unique time. A time when data—big or small—is forcing us to rethink everything, challenge the status quo, and solve problems we previously thought unsolvable. This paper shares a few areas we find big data, making big influences.
Cyber security has become the topic of conversation for organizations across every industry. With the average breach costing $200 per lost customer record, and even more for lost intellectual property, organizations are looking for new solutions. Forward-thinking organizations have discovered a new class of solutions that can detect sophisticated, novel threats designed to look like typical behavior.
Concrete examples of organizations that have used the power of Apache Hadoop to advance the state of their data analytics and create efficiencies or advantages.
Explore traditional ingestion and data processing architectures and new modern approaches using Cloudera.
This report analyzes the attributes of IoT risk by industry. The framework provided helps enterprise security and risk professionals predict when the products they are building, or the technologies they use, will likely become targets of attack.
Learn why organizations are turning to Cloudera’s enterprise data hub, powered by Apache Hadoop, to modernize their cyber security architecture, detect advanced threats faster, and accelerate threat mitigation.
Data is transforming businesses, reducing business risks, and creating a competitive advantage for those who use it effectively.
True Corporation has created a unified and governed enterprise data platform to deliver a 360-degree, omni-channel view so that it can deliver greater value through more relevant offers and services. Thanks to the solution’s ease of use, data scientists work more efficiently, finding it simpler to integrate multiple data streams and discover new trends and patterns to support business development.
Odyssey has implemented predictive models that leverage streaming data and data at rest to enhance the detection of cyber threats, including botnets, malware, and zero-day exploits. In addition, behavioral models help expose abnormal user activity that may be related to potential malicious activity or insider threats.
Understand your big data and analytics maturity level against industry benchmarks and make data-driven decisions based on organizational goals.
"Hadoop is data’s darling for a reason — it thoroughly disrupts the economics of data, analytics, and data-driven applications."
This IDC study offers IDC analysts' collective advice to IT and business decision makers to consider in their planning for big data and analytics (BDA) initiatives.
Cloudera and Intel jointly commissioned Unisphere Research, a division of Information Today, Inc., to survey IT and corporate line of business managers involved in or responsible for data center operations.
Self-service analytics allow anyone, anywhere to leverage relevant data for improved decision-making - without complicated tools. This white paper answers your important questions: How do I meet the needs of different user communities? How do I make insights action-oriented? Is my data self-service ready? Where does big data fit in? It also features real-world use cases for sharing crucial enterprise information to satisfy a wide range of information consumers.
In this white paper, we show you various ways to unlock the value of enterprise data – including big data and open data – for generating new revenue, realizing significant cost savings, redefining the customer experience, and pretty much changing business as usual.
Quite often, big data projects are left unfinished. Why? Inaccurate scope, technical roadblocks, and data silos are just a few of the reasons. In this white paper, we highlight six issues you need to account for to get the most value from your Hadoop ecosystem. And then we provide best practices that can help you avoid some of the most common mistakes made during Hadoop rollouts, so you can put your big data initiative on the path to success from the start.
To frame big data analytics, you need to identify the purpose of the project, connections to existing data, and the context for the analysis. Master data establishes the context and connections that are absent from most big data analytics. In this white paper, you'll learn how master data management (MDM) and its companion, data governance, can also improve data quality and provide other enhancements to your big data analytics initiative.
The road to a successful master data management (MDM) program can be full of detours and dead ends. In this white paper, Dan Power and Julie Hunt from Hub Designs identify the eight worst practices when planning and designing a MDM and data governance program, and show you to get it right. (Updated for 2016)
This white paper discusses the importance of employing advanced data visualization and data discovery as part of a broader enterprise business intelligence and business analytics strategy. It demonstrates how this approach will expand the scope of analytic capabilities to include self-service reporting and dashboard creation, so employees at all levels of the organizations can uncover insights and measure related outcomes – while leveraging existing tools, talent, and infrastructure.
Traditional approaches to mastering data are long, complicated, and cumbersome endeavors that drain resources - it can take a year or longer to produce a single mastered domain. In this white paper, we discuss the pitfalls and problems of legacy master data management methods, and highlight innovative new approaches. You'll also meet Omni-Gen, a product that simplifies and accelerates the creation and deployment of mastering applications.
Want to know why business intelligence (BI) applications succeed and BI tools fail? Updated for 2016, this white paper presents the five worst practices in BI and analytics – and helps you to avoid them. You'll learn from the experiences of BI experts and information specialists and avoid mistakes such as Worst Practice #1: "Depending on Humans to Operationalize Insights". It's a great guide to help you think through how to use BI to enable a culture where everyone is empowered to make better decisions.
The fact is that after installing and using DB2 for Linux, UNIX and Windows for a while, your organization will inevitably have to decide whether or not to upgrade to a new version or release of the DBMS. How and when you approach upgrading DB2 should rest on multiple factors including the features in the new version, organization’s risk tolerance, and other important criteria. In this white paper, we’ll cover the important factors you need to consider before taking on the challenge.
This whitepaper discusses upgrading to MySQL 5.7 – its enhancements, security plugins and the benefits of upgrading. Also, we explain the various ways to upgrade, the default conflict changes in upgrading from 5.6 to 5.7, and the changes in configuration defaults. Finally, we outline the best practices to use when performing a MySQL upgrade, practices which are fundamental to preventing database applications from breaking during upgrade.
This white paper explores 10 reasons you might need “half a DBA.” But how realistic is that? How can you hire half a person? We examine the conventional difficulties associated with finding exactly the services your organization needs, and propose solutions that will enable your organization to obtain the coverage needed at an affordable price.
Cloud-based database management provides organizations with database expertise when it is needed, where it is needed, and at the scale needed. Having experienced database professionals continuously available, both for ongoing issues and urgent projects, provides organizations with cost efficiencies and increased flexibility. Download this special white paper to learn why and how.
Applications owners can now deploy nearly cost-free real-world Oracle database test & QA database environments for their developers by deploying applications on the Pure Storage FlashArray. This prevents problems from entering production environments and unleashes sustainable business agility.
Data (and database management systems, like Oracle) have never been more critical for competitive advantage. All modern IT initiatives – cloud, real time analytics, Internet of Things – intrinsically need to leverage more data, more quickly. All-flash storage is a next generation infrastructure technology that has the potential to unlock a new level of employee productivity and accelerate your business by reducing the amount of time spent waiting for database and applications.
This short guide provides a crash course into how to quickly analyze AWR reports to identify performance issues, as well as possible infrastructure solutions that can help ensure that those problems are eliminated for good.
Tech pros seek insights and share unvarnished opinions in independent forums all over the web. That’s where this Real Stories project & research started. This report is drawn entirely from Pure Storage Real Users’ words, observations and experiences. All Stories are used with permission.
Read this document to learn how businesses can extract data directly from SAP ERP, CRM, and SCM systems and analyze data in real-time, enabling business managers to quickly make data-driven decisions.
This paper covers the necessary steps to take a snapshot of a SAP HANA instance for backup purposes. It also explains how to restore the database from the snapshot.
How can you modernize and deliver on-demand services while keeping your existing SAP landscape optimized and your risks minimized? Read this document to learn the six incremental steps to SAP HANA implementation.
Read the White Paper titled “Five Signs You May Have Outgrown Cassandra (and What to Do About It)” to determine whether your Cassandra infrastructure is hampering your ability to be agile, to compete, and to bring new products and services to market cost-effectively.
We are living in a new age, one in which your business success depends on access to trusted data across more systems and more users faster than ever before. Whether you’re responsible for technology or information strategy, you need to enable your business to have real-time access to reliable information to make rapid, accurate decisions faster than your competitors. Otherwise, your company will simply be left behind. By taking the actions detailed in this paper, you can create and set in motion a data quality strategy that supports your existing business initiatives and easily scale to meet future needs.
According to a recent survey, business and IT professionals cite “overcoming organizational culture” as the biggest challenge they face when trying to adopt or implement an enterprise data governance strategy. Without effective cross-functional communication and collaboration, you cannot create a culture that embraces data governance as an underlying principle of successful business. Professionals trying to establish a data governance strategy should take advantage of a framework of best practices that identifies business problems and their impact and facilitates a culture of cooperation. Using such a framework as a guide, you can set a data governance strategy in motion, secure executive sponsorship, and realize early success that can support broader initiatives. In this white paper, learn best practices for designing and implementing a successful, long-term enterprise data governance strategy.
Read to learn the key factors that led developers to DBaaS, the challenges of their previous database platforms, and how they’ve been able to get hours back in their day to innovate more and worry less about database management.
Once you know that a document oriented database is the best database for your application, you will have to decide where and how you'll deploy the software and its associated infrastructure. Download this white paper for an outline of the deployment options available when you select IBM® Cloudant® as your JSON store.
We start by discussing the benefits and limitations of Galera clustering and the general guidelines and best practices of implementing Galera Cluster. We continue by examining the state of transfer methods used to update joining nodes with Cluster, outlining Cluster's initial configuration and default communication ports, and discussing the relevance of the Percona's infamous clustercheck script.
Download this special report to under the challenges facing enterprises from Big Data, and the limitations of physical data lakes in addressing these challenges. You’ll learn how to effectively manage data lakes for improved agility in data access and enhanced governance, and discover four key business benefits of using data virtualization to fulfill the promise of data lakes.
The proliferation of data sources, types, and stores is increasing the challenge of combining data into meaningful, valuable information. While companies are investing in initiatives to increase the amount of data at their disposal, most spend more time finding the data they need rather than putting it to work. To truly expand their analytical capabilities, enterprises need new approaches to data integration that enable more flexible, agile, and efficient data management processes. Download this special report to learn about the key developments and emerging strategies in data integration today.
In this Datavail white paper, we explore the rationale for upgrading to Oracle 12c, explain the process of upgrading, and provide a script used for an actual upgrade performed in under an hour.
Although DevOps now covers a broad range of platforms, languages, and processes, it still uses the same series of detailed steps to result in a useful application. Database administrators play an essential role in application development, often taking the lead and helping to accelerate the process by assuming the data architect role. Since all applications are extremely dependent upon data, database administrators are able to field design questions that might otherwise require extensive trial and error.
Avnet delivers new insight to customers in record time with a cloud data warehousing and analytics solution from IBM. A near 100-times boost to reporting performance means customers can find the answers they need faster than ever, helping them take their businesses to new heights of success.
Enterprise data warehouses remain as relevant as ever in today's business environment. However, the traditional data warehouse is not up to the task with a flood of new data pouring in at an increasingly rapid pace. To maintain their competitive advantage, organizations must take action now to modernize the traditional data warehouse.
Technical white paper from IBM dashDB, a cloud-based data warehousing service providing instant access to critical business analytics. It allows users to quickly mine more value from their data and build better solutions and applications, while spending less time and resources building their data warehouse infrastructure.
Join this webcast to learn how Oracle GoldenGate Cloud Service: Enables on-boarding to cloud from heterogeneous systems without interrupting source systems, makes real time transactional data available for operational reporting, data warehousing, and big data analytics in the cloud, and supports production-like dev/test environment by bringing live data from production systems.
Register now and get ready to exploit data beyond the confines of physical data centers
There are many benefits that can be gained by moving database processes off-premises, including consolidating critical applications, analyzing data, enabling insights quickly and effectively running development and test environments in the cloud. The question is: how do you easily extend your data center to the cloud and keep it in sync with critical systems running on premises?
Oracle GoldenGate Cloud Service enables you to move information from mission-critical, on-premises systems to the cloud—in real-time, without compromising the availability or performance of source systems, or the security of your data.
Business decisions are only as reliable as the data that informs them, and just because you’re using corporate data doesn’t mean you’re getting the whole story behind what’s happening within your business. Without the right data discovery approach, you can end up with data chaos, untrustworthy reports, and visualizations that can lead to dubious business decisions.
The field of business intelligence is always changing. What’s ahead? Download this eBook to find out the six critical trends and how users are becoming information activists.
Several obstacles get in the way of confident decision making. Download this white paper for the four steps you can take to reduce unreliable data and increase its trustworthiness.
SharePoint is a Microsoft web application frameworkand platform commonly used for collaboration, but organizations can use it for much more than sharing internal documents. In this white paper we outline six different things you can do with SharePoint beyond basic collaboration to increase productivity and cut application clutter at your organization.
Microsoft's SharePoint is a Web application framework used to create Web pages and for content and document management. If it becomes sluggish, it can affect business productivity and operations. This white paper outlines 10 common user challenges, along with guidelines for resolving them. We also discuss some ancillary tools to help users continue maintaining SharePoint.
SharePoint, Microsoft’s web application framework, is an incredibly powerful tool that can integrate an organization’s content, manage documents, and serve as an intranet or internet website. But it's difficult to recruit, hire, and train the people needed to operate SharePoint at best-practice levels of support around the clock. In this white paper, we describe seven strategic tasks a managed services provider will undertake to ensure your organization has a superlative SharePoint implementation. We conclude with three case histories of SharePoint solutions our clients followed that boosted business value.
This white paper will explore the top five database challenges restaurant chains will face in 2016 and how managed services and remote database management can enable these businesses to harness and make the most of the modern data revolution.
When you say “migrations and upgrades” to a database or systems administrator, what they often hear is “risk and downtime.” It doesn’t have to be that way. Find out how you can simplify the migration and upgrade process to minimize risks and avoid getting stuck in the office after hours.
To compete in our global economy, businesses need to empower their users with faster access to actionable infor¬mation and a better overall picture of their operations and opportunities. At the forefront of this journey to create value from data is in-memory processing. Download this report to learn the latest developments, best practices and case studies.
This new retail business model offers an unparalleled personalized shopping experience to customers that is so effective that 78% of retailers intend to implement it. Sounds great, right? Well, there’s one problem: most retailers are behind! And the difficulty of converting databases to a unified commerce model is one of the main reasons so many companies struggle to make the change. This white paper is dedicated to pinpointing the top three data challenges today’s retailers face in switching to unified commerce, and how Datavail’s managed services can enable you to overcome them and thrive.
This paper demystifies query tuning by providing a rigorous 12-step process that database professionals at any level can use to systematically assess and adjust query performance, starting from the basics and moving to more advanced query tuning techniques like indexing. When you apply this process from start to finish, you will improve query performance in a measurable way, and you will know that you have optimized the query as much as is possible.
For database administrators the most essential performance question is: how well is my database running? Traditionally, the answer has come from analysis of system counters and overall server health metrics. Yet, because the primary purpose of a database is to provide end users with a service, none of these counters or metrics provides a relevant and actionable picture of performance. To accurately assess database instance performance from the perspective of service provided, the question must become: how much time do end users wait on a response? To answer this question, you need a way to assess what’s happening inside the database instance that can be related to end users. Download this special white paper to learn about the response time analysis approach.
Introduced in Microsoft SQL Server 2008, Extended Events are a lightweight event-handling mechanism you can use to capture event information about the inner workings of SQL Server. Extended Events replace SQL Trace as the interface for diagnostic tracing in SQL Server 2012 and later. Download this white paper to learn how you can ruse Extended Events to improve SQL Server Performance Management.
Currently, scale-out databases lack any viable data recovery solution: one that allows for corrupted data to be removed, replayed, and propagated with minimal downtime to customer-facing applications. Download this checklist to learn the key items to keep in mind when exploring a solution.
Recent years have seen a surge in demand for easy-to-use, agile tools that provide more data analysis capabilities to business users for faster, more accurate decision-making. Both IT personnel and business users agree that business intelligence (BI) solutions should involve more users and facilitate information sharing and collaboration between teams, in order to increase content creation and consumption. This white paper covers how to deploy secure governed self-service analytics.
Splunk’s software is designed to collect, index, categorize, and report on data from a variety of sources. Traditionally known for its use as a network monitoring, or security tool in a what is now a growing field of competing products, Splunk sets itself apart by being more of a framework than an out-of-the-box product. It has a rich feature set that makes it ideal for a variety of instrumentation needs, including database monitoring.
In this white paper, we provide an overview of Splunk’s features and provide examples of the tools a user can employ at no cost using Splunk’s free license version in his or her own enterprise database-driven application.
As Bob Dylan once sang, “The times they are a-changing.” The world of databases is certainly changing. From the rise of NoSQL and NewSQL adoption to the advancement of in-memory and cloud technologies, when it comes to managing data, businesses today have more choices than ever before. Even the long-standing RDBMS is undergoing a renaissance with new capabilities that place it squarely in the big data future.
This change reflects the growing complexity of data environments and business demands. In fact, the subscribers of Database Trends and Applications were recently asked about the most important reasons for adopting new database platforms. Their response was telling. The top drivers were supporting new analytical use cases, improving database flexibility, and improving database performance. Download this special report to understand the database landscape today.
Watch this video for an overview of SAP HANA Vora. Learn how this in-memory query engine allows you to leverage and extend the Apache Spark execution framework to provide enriched interactive analytics on Hadoop.
Organizations want to use big data to enable digital transformation. However, their top challenges are aligning big data initiatives with business goals through unified processing and correlation of internal and external data sources. This white paper from Harvard Business Review explores how companies can make this newly-enriched information available to both business analysts and general knowledge workers in an easy-to-consume way to gain better context for business decisions.
The proliferation of big data generated by enterprise applications, consumer web/mobile apps, and the Internet of Things (IoT) has afforded an unprecedented opportunity for businesses to know more about their customers than ever before. However, most of the potential of big data lies dormant, as most businesses lack the tools and capabilities to effectively access, process, and analyze the data available to them in a timely manner. Read this report, authored by Forrester Research, to learn about the key findings of a recent research study exploring the hypothesis that most businesses are only analyzing a small part of their available data, resulting in significant missed opportunities to better serve customers and improve business outcomes.
For digital businesses that want to infuse business decisions with valuable context from new data sources, SAP HANA Vora is an in-memory query engine that plugs into the Apache Spark execution framework to provide enriched interactive analytics on data stored in Hadoop. Find out how it lets you combine Big Data with corporate data in a way that is both simple and fast.
Find out how you can bridge the divide between enterprise data and Big Data. Our hyper-connected business environment generates new sources of data at an unprecedented rate. The ability to use Big Data stored in Hadoop for deeper insight presents new opportunities for innovation and competitive advantage. Learn how SAP HANA Vora can help you solve the challenge of combining Big Data with evolving digital business processes in a way that is both simple and fast for making in-context decisions.
Jibes saves its clients from upfront analytics software investments by using cloud-based IBM Bluemix and IBM DataWorks solutions to collaborate and build test applications. Client time to insight is reduced by up to 75 percent, and Jibes anticipates a 30 percent increase in revenue.
Today's data-driven organization is faced with magnified urgency around data volume, user needs and compressed decision time frames. In order to address these challenges while maintaining an effective analytical culture, many organizations are exploring cloud-based environments coupled with powerful business intelligence (BI) and analytical technology to accelerate decisions and enhance business performance.
Today's data-driven organization is faced with magnified urgency around data volume, user needs and compressed decision time frames. In order to address these challenges while maintaining an effective analytical culture, many organizations are exploring cloud-based environments coupled with powerful business intelligence (BI) and analytical technology to accelerate decisions and enhance business performance.
The desire to compete on analytics is driving the evaluation of new technologies on a large scale. Many businesses are currently starting down the path to modify their existing environments with new platforms and tools to better connect the dots between the data world and the business world. However, to be successful, the right mix of people, processes and technologies needs to be in place. This requires an analytical culture that empowers its users and improves its processes through both scalable and agile systems. Download this special report to learn about about the key technologies, strategies, best practices and pitfalls to avoid in the evolving world of BI and analytics.
Liberating your mainframe data for bigger insights is critically important, but doing it alone isn’t easy. Download this guide to learn best practices to access and integrate Mainframe data by getting it into Hadoop - in a mainframe format - and work with it like any other data source!
Use this guide to help your organization develop, document and implement a foundation for change management that adheres to COBIT control practices while meeting the needs of internal and external stakeholders.
See how to simplify audit change management, define key control objectives, demonstrate and report on change management compliance, and pass compliance audits.
Avoid common hurdles that can impede your change management results. Learn how to define an effective change management process that reduces the potential risks associated with your ERP application changes.
Download the case study today and learn how a dynamic data discovery platform will allow you to manage every aspect of your business and fuel your company’s growth.
This report argues that top-down and bottom-up BI are flip sides of the same coin and explains that organizations must devise organizational, architectural, and technical frameworks to harmonize these polar opposites. The report then describes the rise of data discovery tools as a bottom-up reaction to heavy-handed BI teams and traditional enterprise BI tools. Data discovery tools have crushed the top-down camp’s monopoly of BI, but in so doing, they have unleashed a bevy of data silos and inconsistent reports.
This O'Reilly Media report provides a roadmap for how to connect systems, data stores, and institutions.
- Identify stakeholders: build a culture of trust and awareness among decision makers, data analysts, and quality management
- Create a data plan: define your needs, specify your metrics, identify data sources, and standardize metric definitions
- Centralize the data: evaluate each data source for existing common fields and, if you can, minor variances, and standardize data references
- Find the right tool(s) for the job: choose from legacy architecture tools, managed and cloud-only services, and data visualization or data exploration platforms
In the overall mobile market, there has been relatively little business-focused M&A activity; most has been around consumer applications and services. However, many large enterprise IT vendors have been investing significantly in mobile services over the past few years. The ob¬stacles that enterprises face in fragmented pure-play marketplaces are leaving the door open for incumbents to drive M&A activity and technology consolidation.
Discover the essentials of optimizing SQL Server management within your organization. Read our e-book and learn to assess your SQL Server environment, establish effective backup and recovery, and maintain SQL Server management optimization.
Meeting new business objectives doesn’t have to result in capital expenditures and SQL Server sprawl. Learn from this paper how you can efficiently maximize database capacity and spend money more strategically to get the most out of your existing IT assets.
Performance optimization on SQL Server can be a challenge. Discover how the 10 tips you need to maximize SQL Server performance, and immediately apply the practical knowledge outlined in this paper within your SQL environment.
IT environments continue to grow in complexity. With multiple database platforms, cloud technologies and enormous volumes of data—DBAs are faced with increased demands from users to proactively find and address performance issues, even as budgets tighten. Read this paper to learn how the right tools can help you identify and correct performance problems before they become critical.
DBAs need access to timely, detailed information in order to act, rather than information that requires further investigation. Read this paper and learn how to leverage event notifications and extended events to monitor in SQL Server, and discover how to these tools enable you to act on issues and avoid outages.
Today, the world of decision making, along with the data sources and technologies that support it, is evolving rapidly. The future of data warehousing is not only being shaped by the need for businesses to deliver data faster to more users but also by the need for a richer picture of their operations afforded by a greater variety of data for analysis. A new generation of technologies and strategies has emerged to meet these requirements. Download this special report to gain a deeper understanding of the current technology landscape, key challenges, and critical success factors in data warehousing today.
Cloudant's managed service is designed to scale and support your fast-growing data management needs. The engineers at Cloudant tune, grow (or shrink) clusters, repartition and rebalance data, and monitor your data 24x7.
Hothead Games Big Win Soccer had been built on Apache CouchDB, and they sought out a faster and more scalable alternative. They chose Cloudant...
The database you pick for your next application matters now more than ever. It can be difficult, and oftentimes impossible, to quickly join today's data into the relational model. Learn how a NoSQL database can act as a viable alternative to or compliment an existing relational database.
Unfortunately, most CMDBs are filled with data that’s outdated, inconsistent, or incomplete. Without clean data, you can’t get the results you want and need from your CMDB.
It’s not your fault. The problem isn’t the CMDB software or the processes you use to populate and manage the CMDB. It’s simply an unfortunate side effect of the complex, ever-changing IT world.
Read this white paper to learn the five data quality problems in every CMDB and what you can do about them.
EMA research documents obstacles to, and options for, achieving an accurate and meaningful ITAM record across IT silos, how an effective ITAM record positively impacts critical business-driven IT strategies, and attributes of the most successful ITAM and financial management teams.
Learn how to reduce or even eliminate a true-up from a software license audit by speeding up and simplifying the collection, reconciliation and reporting of your software entitlement and deployment data.
This technical white paper explains how IBM MobileFirst Platform can address some of the unique security challenges of mobile applications.
To gain insight into successful mobile application development practices today, the IBM CAI surveyed 585 developers and development managers from nine countries. How do some projects deliver great applications? The secret lies in having the right team and the right approach.
Join Forrester and IBM to learn how, clients are leveraging mobile and cloud to transform their businesses and bring new innovations to market. Understand how organizations can continuously deliver high quality mobile enterprise applications that leverage Cloud computing to securely integrate with their IT systems opening up new sources of revenue and innovation. Forrester Principal Analyst John M. Wargo will share insights Forrester has gleaned from conversations with clients deploying packaged solutions and building custom applications using cloud services. IBM's Botond Kiss will provide insight into how leading organizations are using cloud to accelerate their mobile transformation.
Watch this webinar on the topic of Upgrading to Oracle Database 12c.
This paper describes the “finger-pointing” challenge faced by DBAs and how the advanced and unique capabilities of Foglight for Databases enable DBAs to meet that challenge.
Get all the information you need to optimize your databases so you can focus on strategic business initiatives.
The Performance Investigator (PI) feature of Foglight for Oracle helps you achieve optimal database performance by providing comprehensive database, storage and virtualization monitoring, as well as advanced workload analytics. While database resource monitoring ensures that database components operate within their limits by alerting database administrators (DBAs) when they’re overextended, transaction workload analysis measures and analyzes the SQL statements that connect users to resources, enabling effective management of database service levels. Foglight PI integrates both to deliver a seamless workflow.
Get a wealth of information at a fraction of the impact of conventional collection methods.
Foglight’s SQL Performance Investigator (PI) ensures optimal database performance with comprehensive database, storage and virtualization monitoring, along with advanced workload analytics. It integrates transaction workload investigations with database resource monitoring for a seamless workflow. While database resource monitoring ensures that database components operate within their limits — and alerts database administrators (DBAs) when they’re overextended — transaction workload analysis measures and analyzes the SQL that connects users to resources, enabling management of database service levels.
Founded in 2008, and based in Los Angeles, California, AppAdvice provides a wide range of iPhone, iPad, and iPod touch application reviews, news, and app discovery services to help online and mobile visitors discover interesting and new iOS apps.
There is no one-size-fits-all solution. Without knowing the specifics of your organization’s marketing goals, software developer skills, and application architecture, no software vendor can honestly tell you if their database is the right one. What we can do as IBMis share some common mistakes we have seen and points to consider to help make your next project a success.
In a world where the pace of software development is faster and data and piling up, how you architect your data layer to ensure a global user base enjoys continual access to data is more important than ever.
There are many different permutations of MySQL available; which should you be using? This whitepaper compares and contrasts the major builds, including MariaDB, Percona, and Galera. Benefits and bugs are described, along with recommendations for the best configuration for different database needs.
Which type of database architecture will enable your organization to fully access, manage, and update your data resources through MySQL? This whitepaper discusses storage options; cluster solutions, including Galera and MySQL Cluster; as well as redundancy, speed, failover, and other parameters.
Using NoSQL does not necessarily involve scrapping your existing RDBMS and starting from scratch. NoSQL should be thought of as a tool that can be used to solve the new types of challenges associated with big data. Download this white paper to understand the key issues NoSQL can help enterprises solve.
Traditionally, Oracle has been a quiet participant in the storage market, owning assets from the Sun Microsystems acquisition such as tape storage. As Oracle has invested in Software-as- a-Service (SaaS) software and its customers have asked Oracle to operate this SaaS software for them (in the Oracle Cloud), Oracle has gone back to the drawing board and introduced a brand new cloud-based storage offering for customers and for itself.
When deploying flash technology, the most efficient system is one that performs data reduction techniques inline. George Crump offers criteria to help IT pros decide whether performance or function is most important when choosing all-flash storage arrays.
While hybrid flash arrays are the most popular way to deploy solid-state storage in enterprises, demand for all-flash arrays is growing. Flash is deployed to address storage performance problems for specific applications— typically databases, applications running on virtual servers or virtual desktop implementations. Hybrid arrays make sense for many organizations, because the hottest, most active data is a small chunk of the data on primary storage.
Backing up transactional databases such as Oracle is often viewed as a complicated matter. Of particular concern is making sure the appropriate type of backup solution is in place and, importantly, that backups are actually working meaning they can ultimately be recovered. As the saying popularized by storage strategy guru Fred Moore goes, “Backup is one thing…recovery is everything.”
This IDC Flash summarizes Oracle's August 27, 2015, announcement of the new All Flash FS, heralding Oracle's entry into the rapidly growing all-flash array (AFA) market that IDC thinks will dominate primary storage solutions by 2019 and discusses the importance of the announcement for both Oracle and non-Oracle customers.
There is a good reason the majority of the Forbes Global 2000, as well as government organizations and thousands of companies in diverse industries worldwide, trust theirenterprise data assets to ERwin - we get the hard stuff right. From enterprise data standards, to data governance authoring and control, to flexibility and customization, to data model governance, to web-based publication and reporting, see why organizations trust ERwin to manage their enterprise data. With a variety of tools to help manage multiple data sources used by disparate users and roles, ERwin helps foster collaboration - by governance and design.
Since the early 2000's there has been a combination of factors that has challenged the business world to engender a greater awareness about the quality and usability of information. Examples include recovering customer trust in the wake of financial scandals as well as facilitating the creation of public data sets resulting from government mandates for data transparency. In turn, these activities that must be contrasted with organizations seeking to adopt big data management platforms to analyze massive data volumes to create corporate value.
As combinations of both internal and externally-imposed business policies imply dependencies on managed data artifacts, organizations are increasingly instituting data governance programs to implement processes for ensuring compliance with business expectations. One fundamental aspect of data governance involves practical application of business rules to data assets based on data elements and their assigned values. Yet despite the intent of harmonizing data element definitions and resolution of data semantics and valid reference values, most organizations rarely have complete visibility into the metadata associated with enterprise data assets.
Disruptive forces are radically changing the face of enterprise information management. While the prior generation of information management professionals might have been satisfied with augmenting the organization’s transactional systems with data warehouses supporting reporting and analytics, today’s data practitioner is faced with three factors that are influencing the evolution of the organizational enterprise information management paradigm: Analytics-driven processes, Expanding external user community, and Broadened data inclusion.
Today, more than ever, businesses rely on IT to deliver a competitive edge. They want efficiency, agility, and the ability to innovate through better collaboration, visibility, and performance. However, as data sources, workloads, and applications continue to grow in complexity, so does the challenge of supporting them. To be successful, businesses need faster, more flexible, and more scalable data management processes.
Download this special report to gain a deeper understanding of the key technologies and strategies.
Data is now a critical differentiator in nearly every industry. Organizations on the leading edge of data management are able to achieve greater profitability and compete more effectively. To stay ahead, you need a database management system that will accommodate relentless growth, support increasingly faster decision-making, and deliver breakthroughs in performance, security, availability, and manageability.
Enter Oracle Database 12c, the next generation of the world’s most popular database. It’s built on a new multitenant architecture that enables the deployment of database clouds. A single multitenant container can host and manage hundreds of pluggable databases to dramatically reduce costs and simplify administration. Oracle Database 12c also includes in-memory data processing capabilities delivering breakthrough analytical performance to power the real-time enterprise.
In order to derive business value from Big Data, practitioners must have the means to quickly (as in sub-milliseconds) analyze data, derive actionable insights from that analysis, and execute the recommended actions. While Hadoop is ideal for storing and processing large volumes of data affordably, it is less suited to this type of real-time operational analytics, or Inline Analytics. For these types of workloads, a different style of computing is required. The answer is in-memory databases.
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
Is your data architecture up to the challenge of the big data era? Can it manage workload demands, handle hybrid cloud environments and keep up with performance requirements? Here are six reasons why changing your database can help you take advantage of data and analytics innovations.
The Internet of Things represents not only tremendous volumes of data, but new data sources and types, as well as new applications and use cases. To harness its value, businesses need efficient ways to store, process, and ana¬lyze that data, delivering it where and when it is needed to inform decision-making and business automation. Download this special report to understand the current state of the marketplace and the key data management technologies and practices paving the way.
Underpinning the movement to compete on analytics, a major shift is taking place on the architectural level where data is captured, stored, and processed. This transformation is being driven by the need for more agile data management practices in the face of increasing volumes and varieties of data and the growing challenge of delivering that data where and when it is needed. Download this special report to get a deeper understanding of the key technologies and best practices shaping the modern data architecture.
If you’re still running an older version of SQL Server, now is the time to upgrade. SQL Server 2012 offers several useful new features that will make the trouble of upgrading worth your while, including new functions to optimize performance and features to improve security.
The first step is to assess the current state of your server and develop a plan for upgrading and migrating your data. There are a couple of ways to do this, each of which we discuss.
Get your copy of the first comprehensive study on data lake adoption and maturity. By surveying both current and potential users in the marketplace, this new study from Unisphere Research and Radiant Advisors documents the key perceptions, practices, challenges and success factors in data lake deployment and usage.
Today, more than ever, businesses rely on IT to deliver a competitive edge. They want efficiency, agility and the ability to innovate. However, the reality is most IT departments are struggling just to keep the lights on. A recent Unisphere Research study found that the amount of resources spent on ongoing database management activities is impacting productivity at two-thirds of organizations across North America. The number one culprit is database performance.
Since its early beginnings as a project aimed at building a better web search engine for Yahoo — inspired by Google’s now-well-known MapReduce paper — Hadoop has grown to occupy the center of the big data marketplace. Right now, 20% of Database Trends and Applications subscribers are currently using or deploying Hadoop, and another 22% plan to do so within the next 2 years. Alongside this momentum is a growing ecosystem of Hadoop-related solutions, from open source projects such as Spark, Hive, and Drill, to commercial products offered on-premises and in the cloud. These next-generation technologies are solving real-world big data challenges today, including real-time data processing, interactive analysis, information integration, data governance and data security. Download this special report to learn more about the current technologies, use cases and best practices that are ushering in the next era of data management and analysis.
The value of big data comes from its variety, but so, too, does its complexity. The proliferation of data sources, types, and stores is increasing the challenge of combining data into meaningful, valuable information. While companies are investing in initiatives to increase the amount of data at their disposal, most are spending more time finding the data they need than putting it to work. Download this special report to learn about the key developments and emerging strategies in data integration today.
When asked recently about their top reasons for adopting new technologies, the readers of Database Trends and Applications all agreed: supporting new analytical use cases, improving flexibility, and improving performance are on the short list. To compete in our global economy, businesses need to empower their users with faster access to actionable information and a better overall picture of their operations and opportunities. At the forefront of this journey to create value from data is in-memory processing. Download this special report to learn about the latest developments surrounding in-memory data management and analysis.
Download this special report to guide you through the current landscape of databases to understand the right solution for your needs.
From fraud detection to ad targeting, supply-chain optimization to campaign forecasting, the key use cases for big data require a successful analytics program. Businesses are investing heavily in initiatives that will increase the amount of data at their fingertips. In fact, the percentage of organizations with big data projects in production is expected to triple within the next 18 months according to a recent study from Unisphere Research. However, many businesses are spending more time finding needed data rather than analyzing it. To compete on analytics, the right mix of people, processes and technology needs to be in place to generate value. Download this special report to learn about the key technology solutions and strategies for succeeding with big data analytics today.
Today, the world of decision-making, along with the data sources and technologies that support it, is evolving rapidly. The future of data warehousing is not only being shaped by the need for businesses to deliver faster data access to more users, but the need for a richer picture of their operations afforded by a greater variety of data for analysis. A new data warehousing architecture is emerging, along with a new generation of technologies and best practices, to support the requirements of big data and the need for faster decision-making. To learn about the new technologies and strategies paving the way, download this special report today.
The “pie-in-the-sky” days of big data may be over, but the urgency for businesses to compete on analytics is stronger than ever. In fact, the percentage of organizations with big data projects in production is expected to triple within the next 18 months based on a recent study from Unisphere Research. The conversation around big data is shifting, from why to how. How can businesses harness the bits and bytes of data being captured inside and outside their enterprise to improve, empower and innovate? To learn about the key big data success stories today, download this special report.
The hottest term today—the “Data Lake”—is currently coming off the hype cycle and into the scrutiny of pragmatic IT and business stakeholders. As with all big concepts that have transformed the industry, from the early days of data warehousing and business intelligence, to the growth of cloud computing and big data, best practices are ultimately proven to deliver the benefits promised. To clarify the ambiguities surrounding the concept of the Data Lake, Unisphere Research and Database Trends and Applications combined forces with Radiant Advisors to publish a comprehensive report, “The Definitive Guide to the Data Lake.” By combining an analysis of fundamental information management principles with existing customer implementations of big data and analytics, this report explains how current data architectures will transform into modern data platforms. Download your copy today.
Sponsored by industry-leaders Hortonworks, MapR, Teradata and Voltage Security
From hybrid databases that can process structured and unstructured data - and run transactions and analytics - in the same location, to hybrid data architectures that bring together both established and new database approaches to address the requirements of different data sources, workloads and applications, the reality that most organizations are facing today is that the world of big data is a multifaceted one. To be successful, organizations need speed, scale, flexibility and agility. At the same time, they need ways to keep down costs and complexity. To learn about the key technologies and approaches to hybrid databases and data environments, download this special report from Database Trends and Applications.
Today, there are more things connected to the Internet than people on the planet. From home appliances and cars, to light bulbs and livestock, if you can attach a sensor to it, it can be become part of a universe of physical objects able to communicate and interact digitally. According to estimates, this universe is on track to exceed over 25 billion devices by 2020, not including PCs, tablets and smartphones.
Underpinning the movement to compete on analytics, a major shift is taking place on the architectural level, where data is captured, stored, and processed. This transformation is being driven by the need for more agile and flexible data management processes in the face of increasing volumes and varieties of data.
Whether Hadoop becomes the de facto data management platform of the future or simply a key component in a hybrid architecture comprised of numerous technologies, one thing is for sure: Hadoop adoption is growing. In fact, a recent survey conducted using subscribers of Database Trends and Applications found that 30% have deployed Hadoop at their organization while 26% are currently considering or planning for its adoption within the next 12 months.
Ask the average DBA how they spend the majority of their time and the answer is almost always going to be “performance tuning.” Optimal performance is a constantly moving target. Database transactions and volumes are constantly growing. Business applications are increasing in sophistication with greater user requirements. To stay competitive, companies want speed, scalability, high-availability and cost-efficiency. The challenge, of course, is getting there.
Many IT departments are researching new technologies to address these issues, from database monitoring tools, to new types of databases, to virtualization and cloud solutions. In a recent study conducted over 285 organizations across North America, database performance monitoring was ranked the top area ripe for automation. This same study found that migrating or upgrading databases was the top area for investment, followed closely by virtualization and cloud.
Data integration is a crucial part of the equation for any business interested in fully harnessing its information resources. However, data integration challenges are multiplying in step with the growing complexity of data environments. Most organizations today are dealing with an ever-expanding array of data sources and users with varying requirements. Therefore, it is no surprise that integration projects are topping the priority list. In fact, a brand new study conducted over the readers of Database Trends and Applications found that 38% of companies polled had integration projects in production while 30% were planning or piloting projects. Download this special report to learn about the key developments in the marketplace and new solutions helping companies overcome challenges.
In-memory computing is currently racing toward the mainstream and revolutionizing the way enterprises leverage data to support their business requirements along the way. How big is this revolution? Nearly 75% of IT stakeholders at organizations across North America surveyed by Unisphere Research believe that in-memory technology is important to enabling their organization to be competitive. To succeed in today’s economy, businesses need faster data processing, fresher data, and more cost-effective data systems. Download this special report to learn the ins and outs, as well as the key products available in the marketplace.
When it comes to databases, businesses have more choices than ever today. From the longstanding RDBMS, to the growing camps of NoSQL and NewSQL databases, the landscape is becoming increasingly specialized and best-of-breed. This transformation mirrors the plethora of challenges IT departments across industries face today: the need to handle larger data volumes, the need to handle new data types, the need to deliver data faster, the need to support more application users, and the need to operate more cost-effectively, to name a few. Download this special report to read about the current state of the marketplace and learn about the new technologies that are helping businesses address these challenges.
Real-time information processing, a concept that has been around for a long time, has been in vogue lately. One reason for its popularity is the fact that real-time capable technology and online services have become very affordable, even for small businesses. Another factor is that real time has the attention and interest of the boardroom and executive suite. The idea of being able to instantaneously sense and respond to threats and opportunities has a lot of appeal for business leaders vying for an edge in a fiercely competitive global economy. With technology chipping away at the time it takes to gather relevant and accurate data, there’s less need for bureaucratic, hierarchical decision-making structures. Emerging technologies are now becoming part of the enterprise scene—such as in memory technology, cloud, mobile, and NoSQL databases—are bringing more real-time capabilities to the fore.
Business intelligence and analytics has undergone a revolutionary shift over the past few years, a transition that is still working its way through enterprises and their processes. Nowhere is this more evident than in the rapidly changing roles and expectations of information workers—those managing the data, as well as those consuming it.
Cloud databases are on the rise as more and more businesses look to capitalize on the advantages of cloud computing to power their business applications. In fact, a recent Unisphere Research study revealed that 37% of organizations are now using or considering adopting a cloud database.
Elastic scalability, high availability, flexible capacity planning, and self-service provisioning are among the key, sought-after benefits. While traditional concerns about data security and compliance still have some enterprises watching from the sideline, for many enterprises, the advantages of cloud databases are becoming harder and harder to ignore.
Since the 1980S, companies have invested millions of dollars in designing, implementing, and updating enterprise data warehouses as the foundation of their business intelligence systems. The founding principle of the data warehouse was simple: a single version of the truth to support corporate decision making. Today, the world of decision making, along with the data sources and technologies that support it, is evolving rapidly.
The future of data warehousing is not only being shaped by the need for businesses to deliver faster data access to more users, but the need for a richer picture of their operations afforded by a greater variety of data for analysis. The unstructured and semistructured data that companies are collecting from social media, remote sensors, web traffic, and other sources needs to be integrated and combined for analysis to produce valuable insights for better decision making.
Listening to the pundits, you can be forgiven for thinking that the unstructured, “cloudified,” out-of-network data tsunami is poised to sweep through and shake enterprises out of their comfortable, relational worlds. But there’s more to the story than that. Enterprises still, and will likely continue to, rely on relational database systems as their transactional workhorses. These systems continue to evolve and adapt to today’s new data realities. Many relational database and data warehouse environments are opening to unstructured data, running in clouds, and supporting caches that enable real-time— or near real-time—decision making.
The next generation of databases and data platforms is coming into full fruition to help enterprises more effectively store, process, analyze and deliver value from Big Data. This report hones in on the key challenges and opportunities ahead, and provides in-depth information on leading-edge technologies and solutions. Download your copy today to stay ahead of the latest developments in NoSQL, NewSQL and Hadoop.
This DBTA Thought Leadership Series discusses new approaches to planning and laying out tracks and infrastructure, moving to a real-time analytics requires new thinking and strategies to upgrade database performance. What are needed are new tools, new methodologies, new architectures, and a new philosophy toward managing data performance.
Today’s 24/7 enterprises require a well-designed, next-generation data integration architecture. Why is data integration so difficult? For many organizations, data integration has been handled as a dark art over the years, implemented behind the scenes with ad hoc scripts, extract, transform, and load (ETL) operations, connectors, manual coding, and patching. Often, front-end applications to get at needed data are built and deployed one at a time, requiring considerable IT staff time, as well as creating a waiting period for business decision makers. This one-off, manual approach to data integration will not work in today’s competitive global economy. Decision makers need information, at a moment’s notice, that is timely and consistent. However, they are challenged by their organizations’ outdated data integration systems and methods. Often, information may be delayed for weeks, if not months, by the time it takes to develop handcoded scripts to deliver requested reports. The process
Hadoop is marching steadily into the enterprise, but key challenges remain, from manual coding demands to a lack of real-time capabilities and the time it takes to bring a Hadoop project into production. At the same time, brand-new startups and veteran software companies alike are delivering new offerings to the marketplace to make it easier to deploy, manage, and analyze Big Data on Hadoop. From data integration and business intelligence tools to integrated analytical platforms and a new wave of SQL-on-Hadoop solutions, the common goal is to help companies unleash the power of Hadoop for Big Data analytics. Download this special report to learn about the key solutions. Sponsored by MarkLogic, RainStor, Tableau, Qubole, Karmasphere, Appfluent, and Hadapt.
UNSTRUCTURED DATA: Managing, integrating, and Extracting Value While unstructured data may represent one of the greatest opportunities of the big data revolution, it is one of its most perplexing challenges. In many ways, the very core of big data is that it is unstructured, and many enterprises are not yet equipped to handle this kind of information in an organized, systematic way. Effectively capturing and capitalizing on unstructured data isn’t just a technical challenge, it represents an organizational challenge. A flexible and agile enterprise environment—supported and embraced by all business units—will elevate unstructured data processing and analysis to a position in which it can help drive the business. This Thought Leadership Series is sponsored by Objectivity and Database Plugins
THE IDEA OF THE REAL-TIME ENTERPRISE is straightforward: Increase your organizational responsiveness through automated processes and raise organizational effectiveness and competiveness. If your organization can fulfill orders, manage inventory, resolve customer issues, and implement strategies to address changing circumstances faster and more efficiently, your organization is going to be more successful. However, for most enterprises, this is still an unrealized objective. Increasing data volumes, data varieties, and business demands are now stretching the limitations of traditional data management technologies and intensifying the challenge of integrating and analyzing data in real-time. Consequently, many organizations are looking beyond their current IT infrastructures. Download this report to learn about the leading technologies enabling organizations to deliver data across the enterprise in real-time. Sponsored by Oracle, SAP, Objectivity, JackBe and BackOffice Associates.
Cloud databases are on the rise as more and more businesses look to capitalize on the advantages of cloud computing to power their business applications. In fact, a recent Unisphere Research study found that nearly one-third of organizations are currently using or plan to use a cloud database system within the next 12 months. Download this complimentary report, sponsored by NuoDB, GenieDB, 10gen, Cloudant, Progress DataDirect, Clustrix, Objectivity and TransLattice, to gain a deeper understanding of the different types of cloud databases, their unique benefits and how they are revolutionizing the IT landscape.
BIG DATA, a well-used term defining the growing volume, variety, velocity, and value of information surging through organizations-has become more than a buzz phrase thrown about at conferences and in the trade press. Big Data is now seen as the core of enterprise growth strategies. Business leaders recognize the rewards of effectively capturing and building insights from Big Data, and see the greatest opportunities for Big Data in competing more effectively and growing business revenue streams. As the amount and variety of data grows, so do the skills required to capture, manage and analyze this data. This specialized issue of Best Practices from Oracle, Attunity, Couchbase, HiT Software Inc, Progress DataDirect, LexisNexis, Confio and Objectivity focus on a more formidable challenge: making Big Data valuable to the business. Complimentary from DBTA.
The appeal of in-memory technology is growing as organizations face the challenge of Big Data, in which decision-makers seek to harvest insights from terabytes and petabytes worth of structured, semi-structured and unstructured data that is flowing into their enterprises. This special thought leadership series provides context and insight on the use of in-memory technology, and detailed explanations of new solutions from SAP, Tableau Software, Tibco Spotfire, JackBe, Terracotta and MemSQL. Complimentary from DBTA.
Is your organization’s systems and data environments ready for the Big Data surge? If not, you are not alone. A recent study conducted among Independent Oracle User Group members by DBTA’s Unisphere Research finds that fewer than one-in-five data managers are confident their IT infrastructure will be capable of handling the survey of Big Data. This special Best Practices section from DBTA provides context and insight on the need to address this issue now, and detailed explanations of new technologies for dealing with Big Data from Aster/Teradata, MarkLogic, Akiban, Progress/Data Direct, Infinitegraph, HP-Vertica and Denodo. Complimentary from DBTA.
To compete in today’s economy, organizations need the right information, at the right time, at the push of a keystroke. But the challenge of providing end users access to actionable information when they need it has also never been greater than today. Enterprise data environments are not only growing in size, but in complexity - with a dizzying array of different data sources, types and formats. The September 2012 Best Practices in Data Integration, Master Data Management, and Data Virtualization report examines the data integration challenges and opportunities that Big Data is currently presenting data-driven organizations.
With the rise of big data, the database and data management tools market is in a state of flux, the likes of which have not been seen in this sector before. Companies are now awash in big data, and end users are demanding greater capability and integration to mine and analyze new sources of information. As a result, organizations are supplementing their relational database environments with new platforms and approaches that address the variety and volume of information being handled. In this special section in Database Trends and Applications analyst Joseph McKendrick brings you up on current thinking and strategies users and vendors are pursuing to extract value from large, often unwieldy data stores. This is followed by nine separate sponsored content pieces focusing on in-memory, real-time data integration, data virtualization, BI, columnar databases, NoSQL and Hadoop.
The rise of Big Datais challenging many long-held assumptions about the way data is organized, managed, ingested, and digested. However, for many organizations, Big Data is still a new frontier that they have only begun to explore. "Many organizations leave their data to pile up; they are aware of it as a resource but haven't analyzed it. They don't know what's useful and what's worthless." This fourteen-page section from the March edition of Database Trends and Applications is an invaluable resource that provides multiple perspectives on the chief challenges our readers face and the solutions that will enable organizations to begin tapping into the power of Big Data assets.
Key extracts from Database Trends and Applications from the December print edition focus on "Data Security and Compliance".