White Papers

Download the new report to learn: Best practices for evaluating DaaS solutions, how DaaS accelerates application projects, which parts of an organization benefit from a DaaS approach and why key performance indicators for DaaS solutions.

This Market Spotlight examines the trend toward deploying data in the cloud and its associated business benefits. After a brief discussion about the rise of cloud services and increased enterprise dependence on data, the document describes the rising costs of data and the ways that organizations can control these costs.

Download this white paper to learn: the key elements of an application modernization platform, including automatic data delivery and virtualization, how centralized data masking can enable modernization even with regulated and sensitive data, on premises or in the cloud, and how modernization and rationalize can be the catalyst in IT’s transformation from bottleneck to strategic enabler of the business.

Download this white paper to learn: Why ERP upgrades often exceed schedule and budget, key testing requirements for upgrading applications such as SAP and Oracle EBS What Data as a Service (DaaS) is, and how it reduces the cost and complexity of upgrade projects.

Business is dependent upon IT to deliver required applications and services, and these applications and services are dependent upon timely and quality refreshes. By virtualizing the entire application stack, packaged application development teams can deliver business results faster, at higher quality, and with lower risk.

Data virtualization is becoming more important as industry-leading companies learn that it delivers accelerated IT projects at reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines the top 10 qualification questions to ask before and during the proof of concept.

Download this whitepaper to see how Delphix helps organizations accelerate their AWS projects and operate more efficiently in AWS environments

Maintaining several databases exclusively for reporting and analytics increases costs. So how can you pull the relevant data you need for making business-critical decisions from your production database, without affecting performance or productivity?

In this webcast, we’ll show you how to easily replicate changes from an Oracle database to a SQL Server cluster, maintaining real-time images of the source tables or subsets of tables for all your data analytic and archiving needs — whether on-premises, remote or in-the-cloud.

Data benefits your business – but only if it’s fresh. In this brief, see how to replicate real-time data, whether it’s onsite, remote or cloud.

Enterprises are increasingly looking to platform as a service (PaaS) to lower their costs and speed their time to market for new applications. Developing, deploying and managing applications in the cloud eliminates the time and expense of managing a physical infrastructure to support them. Based on interviews with leading analysts, reviews of user feedback, published reports and information from cloud providers, we evaluated the top five PaaS providers and their platforms: Amazon Web Services (AWS) Elastic Beanstalk; IBM Bluemix; Microsoft Azure; Oracle Cloud Platform; and Red Hat OpenShift. Download this special white paper to find out the results.

Are your business owners experimenting with NoSQL databases? Learn what use cases are changing the landscape for enterprise-class database systems as they transform from classic OLTP to Operational DBMS. This report is written by Gartner Distinguished Analyst and VP Donald Fienberg and Research VP Merv Adrian.

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 databases and applications.

Unlock the true potential of your Oracle database and applications with an all-flash storage infrastructure. Learn how flash can not only accelerate database performance, but also simplify database operations and administration, while reducing overall cost of Oracle environments by 30%.

More data has been produced in the last 10 years than all previous decades combined. This increase in data volumes has introduced an entirely new set of challenges for DBAs around performance and availability. To better understand these challenges we carried out a survey of IT decision makers in companies with employees of 500 or more. Check out the results of this survey to see what challenges you share.

Either type of SQL Server upgrade – in-place or side-by-side – is a serious project with many considerations. A smooth, successful upgrade relies on good planning. With that in mind, here are some tips you will want to follow in order to make that transition to a new version of SQL Server.

If you’re still running an older version of SQL Server, now is the time to upgrade. SQL Server 2014 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.

Automation is quickly becoming a critical component of any high-functioning development team. Find out how automating development cycles can help you support agile methodologies and reduce risk

Learn the three principals that will help you create high-quality database applications and achieve true agile development — as well as increase productivity, performance and more.

The data warehouse is an established concept and discipline that is discussed in many books, conferences and seminars. Into this world comes a new technology – Big Data. In this paper, William Inmon describes the differences and similarities between data warehouse architectures and Big Data technologies.

Whether your organization is migrating 10 or 10,000 users in a six-week or six-year project, read this e-book to see how embedded analytics inform your approach to people, processes and technologies, and drive migration success.

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.

This white paper is written for SAP customers evaluating their infrastructure choices, discussing database technology evolution and options available. It is not easy to put forth a black-and-white choice as the SAP workloads straddle both real-time analytics and extreme transaction processing, and infrastructure choices can now be vast, given technology advancements around in-memory and faster processing speeds.

This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support. It also contrasts this approach, taken in a relational database context, with clustering approaches employed by NoSQL databases and Hadoop applications, showing the importance It goes on to discuss the specific advantages offered by IBM's DB2 pureScale, which is designed to deliver the power of server scale-out architecture, enabling enterprises to affordably develop and manage transactional databases that can meet the requirements of a cloud-based world with rapid transaction data growth, in an affordable manner.

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.

This white paper discusses the concept of shared data scale-out clusters, as well as how they deliver continuous availability and why they are important for delivering scalable transaction processing support.

Analyst Mike Ferguson of Intelligent Business Strategies writes about the enhanced role of transactional DBMS systems in today's world of Big Data. Learn more about how Big Data provides richer transactional data and how that data is captured and analyzed to meet tomorrow’s business needs. Access the report now.

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.

The modern-day digital revolution and the rapidly growing Internet of Things (IOT) are creating more data than ever seen before. The variety, complexity, and velocity of this data, and its many sources, are changing the way organizations operate. Read on to learn more about the seven trends driving the shift to data discovery.

Are you getting the most business value from your data? In this new eBook, discover five ways to overcome the barriers to better data analytics.

This Datavail whitepaper examines the benefits and drawbacks of working with MySQL Cluster and compares these to a typical Master/Slave configuration. An alternative to MySQL Cluster and Master/Slave, known as Galera Cluster for MySQL, is also described.

IBM Analytics for Apache Spark for Bluemix is an open-source cluster computing framework with in-memory processing to speed analytic applications up to 100 times faster compared to other technologies on the market today. Optimized for extremely fast and large scale data processing - you can easily perform big data analysis from one application.

Historically, building a data warehouse is a painstaking endeavor. You have to decide on specific data warehousing software and then determine and secure the proper balance of hardware and storage to allocate. After the physical makeup of the data warehouse is determined, you are tasked with building both the physical system and the logical data models. This whole process introduces risk every time the data warehouse is changed, leaving you with new questions and doubts. IBM dashDB is a fast, fully-managed, cloud data warehouse that uses integrated analytics to deliver answers in an instant.

IBM Cloudant is a NoSQL JSON document store that’s optimized for handling heavy workloads of concurrent reads and writes in the cloud; a workload that is typical of large, fast-growing web and mobile apps. You can use Cloudant as a fully-managed DBaaS running on public cloud platforms like IBM SoftLayer or via an on-premise version called Cloudant Local, that you can run yourself on any private, public, or hybrid cloud platform you choose.

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.

As a top executive, the future of the company is literally in your hands, and there is a challenge coming your way: maybe it’s Black Friday/Cyber Monday, or open enrollment, or a viral tweet, or a new product that causes the world to stampede to you all at once. That challenge may be a few hours away—or a few weeks away, and because of that you owe it to yourself, your team and your company to make sure your database is ready and not take anyone’s word for it. This white paper will give you, the C-level executive, the key questions to ask, the key principles to grasp, and the best strategy for turning adversity into opportunity.

This video showcases Donald Feinberg discussing In-Memory Database Technology.

Oracle Database introduced Oracle Database In-Memory allowing a single database to efficiently support mixed analytic and transactional workloads. An Oracle Database configured with Database In-Memory delivers optimal performance for transactions while simultaneously supporting real-time analytics and reporting. This paper discusses best practices for using the Oracle Database In-Memory Advisor.

The Oracle Database In-Memory Service is designed to collaborate with you to develop a comprehensive and practical plan to adopt Oracle Database In-Memory combined with Oracle Multitenant architecture. This service is an essential step for designing an environment that delivers faster Data Warehouses, Analytics, Business Intelligence, Dashboards, and Reporting. This powerful new feature combined with Oracle Multitenant to consolidate your databases is a winning combination for performance, standardization and reduction in hardware resources.

This document briefly introduces Database In-Memory, enumerates high-level use cases, and explains the scenarios under which it provides a performance benefit. The purpose of this document is to give you some general guidelines so that you can determine whether your use case is a good match for this exciting new technology.

This white paper examines the need for enterprises to move beyond the static model that limits business intelligence to the accumulation of operational data into a data warehouse or an operational data store (ODS) and the use of the resulting analytics to make decisions based on data that may be days or weeks old.

In this new era of digital connectivity, whole industries are being fundamentally reshaped as organizations scramble to build new business models, tap new markets and create new sources of competitive advantage. However, in the rush to open up new digital channels, businesses cannot afford to lose sight of the need to identify and engage with individuals using a huge range of mobile devices. Mastering digital identities can transform an organization’s position in the digital economy. This study, sponsored by Oracle, assesses the role identity plays in the digital economy.

One of the biggest problems facing companies is how to avoid the potentially disastrous commercial consequences--and the inevitable media embarrassment--of having customer data stolen and paraded publicly. This paper provides a hands-on walk through Oracle Database Vault with Oracle Database 12c by looking at how some of its features can be used to protect real data in real world organizations.

Cybersecurity is a persistent, all-encompassing business risk. Organizations of all sizes and across industry have suffered massive data breaches. Gain powerful insights into how Identity Management can reduce risk, secure data, as well as, cut costs and help grow the business.

By 2020, 80 percent of access to the enterprise will be via mobile devices or other non-PC devices. While mobility transforms how companies engage with customers and employees, this access does not come without risk. In 2013, mobile malware cases rose 197%, contributing to the current epidemic of data breaches. Download Establishing a Mobile Security Architecture eBook for insight on mitigating the risk while taking advantage of the tremendous benefits mobile offers.

We are in the midst of an epidemic; spending on technology has failed to reduce the risk of a data breach. Effective modern security to mitigate a data breach requires an inside-out approach with a focus on data and internal controls. Glean deeper insight into creating an information security strategy by accessing the joint Oracle and Verizon report on Securing Your Information in the New Digital Economy.

Big Data is transforming the way enterprises interact with information, but that’s only half the story. The real innovations are happening at the intersection of Fast data and Big Data.Why? Because data is fast before it’s big. Fast data is generated by the explosion of data created by mobile devices, sensor networks, social media and connected devices – the Internet of Things (IoT). VoltDB understands this and wrote the book on it: Fast Data and the New Enterprise Data Architecture, by VoltDB Co-founder and Chief Strategy Officer Scott Jarr. Download your complimentary eBook today to learn more about fast data and the new enterprise data architecture—a unified data pipeline for working with fast data - data in motion - and historical Big Data together.

The modern telecommunications data center environment must cater to billions of high frequency events daily. Tapping into the value of data in real-time – the moment it arrives – is a significant opportunity but it requires the ability to track billions of events, generate real-time triggers from those billions of events reflecting the contextual usage and deviation in defined behavior instantaneously. Click here to learn how VoltDB enables Emagine International to capitalize on massive amounts of data in real time.

In a high volume streaming data environment that’s required to handle millions of events, in real-time, a primary goal is to make sure the data infrastructure can not only manage this massive streaming data, but ensure the solution is scalable and easily repeatable. Read the case study about one of the largest and most successful loyalty programs in the world. Using Docker, the solution leverages AWS Elastic Load Balancing to automatically distribute incoming application needs without manual intervention. The result was an integrated, highly scalable 10 million-person loyalty program that can turn data into deployed services quickly and easily; enabling them to respond rapidly to changing needs and insights.

In this whitepaper, we will discuss how key data governance capabilities are enabled by Oracle Enterprise Metadata Manager (OEMM) and Oracle Enterprise Data Quality (EDQ).

Extract value from big data and analytics in three easy steps. See how grouping variables enhances a scatterplot’s usefulness when you read this brief.

Find out how to evaluate new technologies that analyze big data, and discover which features are most useful. Plus, learn how to incorporate big data analytics to drive more effective strategies and decision-making. Read this white paper today.

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.

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.

Historically, building a data warehouse is a painstaking endeavor. You have to decide on specific data warehousing software and then determine and secure the proper balance of hardware and storage to allocate. After the physical makeup of the data warehouse is determined, you are tasked with building both the physical system and the logical data models. This whole process introduces risk every time the data warehouse is changed, leaving you with new questions and doubts. IBM dashDB is a fast, fully-managed, cloud data warehouse that uses integrated analytics to deliver answers in an instant.

Conventional wisdom holds if you operate a technology company, all aspects of IT are easy. After all, technology is your business. But every technology company has a special focus, and most are not database management. Whether you are creating virtual reality headsets or crunching numbers in options markets, dealing with database problems is a diversion from your organization’s core capabilities and focus. Download this special white paper to read about the most common database needs of technology companies and how Datavail can help.

Organizations are utilizing open source relational database systems like Postgres to drive down operational costs and redirect budget for strategic initiatives. The increased maturity, reliability and functionality indicates open source databases are now a viable option for enterprise-class implementations. This webinar discusses why open source is now mainstream and how this can help you dramatically reduce IT costs.

Private clouds and software-as-a-service (SaaS) applications are becoming pervasive across the corporate computing landscape. The sun is rising on a new era of enterprise computing, but integration challenges are casting a shadow on many otherwise successful projects. Dynamic Markets conducted a survey of more than 1,300 senior business managers to uncover trends in these technology implementations. The researchers came away with some alarming statistics.

The rapid shift from on-premise applications to a hybrid mix of Software-as-a-Service (SaaS) and on-premise applications has introduced big challenges for companies attempting to simplify enterprise application integration. Download this white paper to learn five ways to simplify cloud integration.

Developing simple mobile applications is commonplace, but connecting those apps to backend systems and services can get complicated. Most mobile analysts estimate that up to 80 percent of mobile app development efforts are devoted to securing and integrating front-end mobile functionality with back-end enterprise information systems.

In order to help customers reduce the cost of developing, testing, and deploying applications, Oracle introduced a broad portfolio of integrated cloud services. These subscription-based platform as a service (PaaS) offerings allow companies to develop and deploy nearly any type of application, including enterprise apps, lightweight container apps, web apps, mobile apps, and more.

What do IT executives look for in cloud service and platform providers? Which capabilities, technologies, and services are most important? How do organizations prioritize performance, management, interoperability, and migration as they consider new cloud implementations? To answer these and other pressing questions, Computerworld worked with Triangle Publishing Services to conduct a global survey of IT professionals in midsize to large enterprises that have experience with public and private clouds.

Data visualization is often described as part art, part science. The rapid introduction of user-friendly features and functionality in BI and analytics solutions is enabling more users than ever before to explore, create, and share insight, making data visualization a must-have tool for the modern data analyst. However, alongside this creative freedom comes a required awareness of the importance of visual design for cultivating meaningful and accurate data visualizations as an analytic asset. This special report will guide you through the best practices for creating meaningful data visualization at your organization.

Oracle Database 12c contains many new capabilities including Oracle Multitenant, in-memory column stores and much more. Oracle Real Application Testing gives you verifiable functionality and performance testing capabilities to take advantage of all the new enhancements. Combining your database upgrade with Oracle Real Application Testing assures you that your database will perform as required, whether you’re implementing an in-memory column store, consolidating to a database as a service model, or doing an in-place upgrade.

As an IT operations professional, your job is more critical than ever because cloud operations are now a fact of life. For example, you must address the concerns of corporate compliance auditors one minute, and the next minute, deal with end users who signed up for cloud services without consulting you first. So, what are you to do? Not to worry! Oracle provides a single solution for managing both situations. Oracle Enterprise Manager 12c provides a “single pane of glass” that allows you to manage on-premises and cloud-based IT using the same familiar interface you know and use on-premises every day.

Oracle Enterprise Manager is Oracle’s integrated enterprise IT management product line and provides the industry’s first complete cloud lifecycle management solution. Oracle Database 12c along with Oracle Enterprise Manager Cloud Control 12c allows organizations to adopt new technologies quickly while minimizing risk. Oracle Enterprise Manager’s business-driven IT management capabilities allow you to quickly set up, manage and support enterprise clouds and traditional IT environments from applications to disk.

Hybrid cloud uptake is on the rise, and the challenges of managing business-driven IT environments, in which public and private clouds can thrive, are becoming increasingly important and critical. How can you manage a hybrid cloud as one cohesive entity when the journey to cloud is so complex? How do you enable lines of business to consume IT services on-demand when you have competing stakeholder priorities? How do you manage multiple clouds when there’s a lack of insight and visibility?

The journey to the cloud is complex, but enabling lines of business to consume IT services on demand is well worth this transformation. However, you'll still have to overcome the perceived problems with the cloud and the often competing priorities amongst stakeholders.

Watch this demo to learn the benefits Oracle Database Backup Service offers your organization. Oracle Database Backup Service is a secure, scalable, on-demand storage solution for backing up Oracle databases to the Oracle Cloud.

Part of the Oracle Cloud PaaS portfolio, Oracle Database Backup Service is a cloud-based storage solution for Oracle Database backups that can be used to consolidate storage infrastructure or as an integral part of a multitier database backup and recovery strategy. Download this special solution brief to understand how it works, the benefits and use cases.

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.

While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.

This e-book explores five critical steps that will help organizations streamline their application infrastructure, reduce infrastructure costs and transform enterprise data into a trusted, high-value resource by successfully consolidating and retiring their applications.

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.

To meet the business imperative for enterprise integration and stay competitive, companies must manage the increasing variety, volume and velocity of new data pouring into their systems from an ever-expanding number of sources. They need to bring all their corporate data together, deliver it to end users as quickly as possible to maximize its value, and integrate it at a more granular level than ever before—focusing on the individual transaction level, rather than on general summary data. As data volumes continue to explode, clients must take advantage of a fully scalable information integration architecture that supports any type of data integration technique such as ETL, ELT (also known as ETL Pushdown), data replication or data virtualization. Read this new whitepaper to learn about the seven essential elements needed to achieve the highest performance

The Internet of Things is driven by consumer demand for new services and convenience, as well as by the availability of low cost sensors smart phones, and universal internet access, offering tremendous growth opportunities and new revenue streams. New technologies can enable you to take advantage of this new natural resource through gateway processing, cloud infrastructure and distributed real-time analytics. Listen to the webcast to hear about the latest technology enabling the Internet of Things across devices, sensors, gateways and the cloud for connected environments. See how bringing an intelligent mix of technologies from an enterprise-class database to the “edge”and real-time analytics on consolidated data provides a competitive advantage in the Internet of Things.

This report examines the potential that the IoT offers in enabling organizations to develop deeper, more fine-grained and timely insight from the massive volume of data that it will generate and the steps that organizations need to take in order to drive new insight from big data.

IBM and Intel gateway solutions bring real-time intelligence to the Internet of Things. Finally, your business can reliably store, access and analyze data from billions of connected devices on the edge - and answer the toughest questions, faster than ever.

Are you ready for the Internet of Things? IBM Informix offers an intelligent, enterprise-class database with key capabilities to address the data management challenges of big data, cloud and mobile computing.

The 12c version of Oracle Data Integrator pushes this state of the art technology in data integration further ahead of the rest of the industry. Oracle continues to invest on this strategic data integration platform. This whitepaper describes in detail some of the new features and capabilities offered in the Oracle Data Integrator 12c platform.

Oracle GoldenGate for Big Data 12c product streams transactional data into big data systems in real time, without impacting the performance of source systems. It streamlines real-time data delivery into most popular big data solutions, including Apache Hadoop, Apache HBase, Apache Hive, and Apache Flume, and facilitates improved insight and timely action.

To explore the differences among the leading data integration solutions and the impact their technologies are having on real-world businesses, Dao Research recently conducted a research study, where they interviewed IBM, Informatica, and Oracle customers. In addition they reviewed publicly available solution information from these three vendors. I invite you to read this research paper by Dao to understand why more and more customers trust Oracle for their strategic data integration initiatives after working with or evaluating competitive offerings.

The success of any big data project fundamentally depends on an enterprise’s ability to capture, store and govern its data. The better an enterprise can provide fast, trustworthy and secure data to business decision maker’s the higher the chances of success in exploiting big data, obtaining planned return on investments and justifying further investments. In this paper, we focus on big data integration and take a look at the top five most common mistakes enterprises make when approaching big data integration initiatives and how to avoid them.

Oracle Data Integrator Enterprise Edition Big Data Options brings speed, ease of use and trust to how enterprises capitalize on data. Big data management is essential to any organization that wants to make serious headway in their decision making culture. Data is being generated in all forms, from various traditional and nontraditional sources to provide competitive advantages. Oracle Data Integrator for Big Data addresses this growing need in the market by providing a future proof, powerful platform to build your enterprise around its Data Management framework.

Your IT infrastructure is critical, and keeping it running efficiently can take a toll on your team, especially if they are spending all their time on low-level, day-to-day tasks, instead of the strategic growth of the business. Gaining operational control of your IT infrastructure assets - and turning IT into a strategic differentiator - gives you the power to concentrate your team’s talents on driving business instead of performing maintenance. Download this whitepaper to learn more

Today’s database administrators are challenged with the need to prioritize managing round-the-clock critical functionality, addressing increasingly expanding volumes of data and consulting with end-users to design new applications. But low-level, day-to-day tasks can distract from that, which is why many CIOs are shifting to outsourced or managed service solutions to handle the basic-but-critical tasks.

Download this complimentary white paper today to learn about the drivers shaping the future of analytics. Also, get a real-world example of how one company is using cloud-based analytics to save money and improve patient care.

Read this white paper to get a better understanding of the scale out database landscape and considerations to identify best solution for your business.

In this ebook, Noel Yuhanna, Principal Analyst at Forrester Research and lead author of the recently published, The Forrester Wave™: Enterprise Data Virtualization, Q1 2015 report, explains the most up-to-date research on data virtualization – fresh trends, hot use cases and innovations and why it is essential for modern data architectures. This ebook also includes real-life examples from large and complex deployments of data virtualization.

Database Mail is a simple feature available to users of ordinary email accounts that can be configured to send automated alerts and scheduled reports concerning database performance. Just as you create calendar reminders to alert you of scheduled meetings, you can use SQL Server to perform similar functions. You can receive an alert when a new database is created, or get an email if a key performance indicators (KPI) has changed. Say you would like to receive a spreadsheet every morning with the quantities sold for every product? Database Mail allows you to do that. This Datavail whitepaper will show you step-by-step, how to enable Database Mail, and will then provide you with sample scripts you can customize to create automated alerts and scheduled reports.

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.

Assessing the quality of remote database administration is not a trivial task. Datavail’s goal is to exceed client expectations on each and every call with one of our database administrators. This white paper details the 9 metrics Datavail uses for ticket quality evaluation.

Microsoft Power BI is a self service solution for your data needs using Excel. It incorporates different tools for data discovery, analysis and visualization. Based in the cloud it provides you insight into almost any type of data in Excel, which is one of a DBAs best tools. Excel has evolved so much over the years it’s difficult to stay abreast of additions and fancy tools. With the introduction of a number of Power capabilities including Power Pivot, Power View and Power Maps, it’s Excel’s Power Query that’s worth looking into further. Power Query helps end users find and prep data for analysis. Power Query makes it possible for queries to be published and reused, but the script is easier to maintain. In this white paper we will look at Power Query’s shaping capabilities when working with data inside Excel 2013.

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.

The ten-page report names four cool vendors, noting: “The analytics market continues to diversify, with a variety of emerging vendors targeting increasingly specific problems that organizations possess. The analytics market continues to be one that readily lends itself to innovation, and the growing demand for analytic capability across all parts of organizations creates a growing opportunity for vendors to offer compelling new solutions.”

This research case study will explain how Warby Parker has gone from a company that was run entirely out of an ERP, to one in which the company's decision are powered by precisely-defined and integrated data model. This story will cover the use of various technologies to create a data warehouse and the use of Looker to create an integrated model that supports discovery, analysis and automation as well as the propagation of data to every corner of the company.

Quick iteration and reusability of metric calculations for powerful data exploration. At Looker, we want to make it easier for data analysts to service the needs of the data-hungry users in their organizations. We believe too much of their time is spent responding to ad hoc data requests and not enough time is spent building, experimenting, and embellishing a robust model of the business. Worse yet, business users are starving for data, but are forced to make important decisions without access to data that could guide them in the right direction. Looker addresses both of these problems with a YAML-based modeling language called LookML.This paper walks through a number of data modeling examples, demonstrating how to use LookML to generate, alter, and update reports—without the need to rewrite any SQL. With LookML, you build your business logic, defining your important metrics once and then reusing them throughout a model—allowing quick, rapid iteration of data exploration, while also en

This Guide will help you make the most of Redshift for Analytics, download today and learn important tips and must-knows when setting up a data warehouse on Redshift.

The rapid explosion of Big Data is changing the landscape of the IT industry. And this data is becoming so important for today’s businesses, as it contains customer insight and growth opportunities that have yet to be identified. Download this complimentary white paper and learn how you can easily manage, understand and leverage all forms of Big Data in real time to discover new opportunities and increase revenue.

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.

As data structures get more complex and data volume continues to accelerate within the enterprise, organizations have been presented with enormous opportunities to transform their businesses at scale. Whether it is production data collected from factory machines, GPS data streamed from delivery vehicles, metrics gathered from website traffic or even completely unstructured caches of customer social media posts, today’s endless sources of data hold tons of potential value for business leaders.

Data warehousing and Business Intelligence (BI) are the mainstays of traditional information architecture and integration. However, innovative and disruptive data technologies, increasing data volumes and sources of data, more complex data integration and quality issues, and the need for lower data latencies are forcing data architects to change how they approach tomorrow’s information architecture. While these latter developments do shake up the status quo, they do not mean the traditional data warehouse (DW) is no longer needed. Instead, data architects must extend the current DW architecture beyond its established "walls" to embrace new data management approaches in a consistent and seamless manner.

Glynn Bird discussed the performance tradeoffs of NoSQL and relational databases, data modeling in a schemaless system, common transactional architectures for applications built on NoSQL, and when you should consider managed, hosted solutions like Cloudant in this webinar.

Join Ryan Millay, IBM® Cloudant® Sales Engineer, to discuss what you need to consider when moving from world of relational databases to a NoSQL document store in this webinar.

Why use NoSQL? Watch this webinar for a discussion about the design decisions you should consider when vetting NOSQL as the back end for your application, learn when NOSQL is the right solution and when it’s not

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.

While successful mobile apps can elevate and transform your brand, hidden deployment disasters can tear down all your hard work in the blink of an eye.

Apache Hadoop didn’t disrupt the data center, the data did. Shortly after Corporate IT functions within enterprises adopted large-scale systems to manage data, the Enterprise Data Warehouse (EDW) emerged as the logical home of all enterprise data. Today, every enterprise has a data warehouse that serves to model and capture the essence of the business from their enterprise systems. The explosion of new types of data in recent years – from inputs such as the web and connected devices, or just sheer volumes of records – has put tremendous pressure on the EDW. In response to this disruption, an increasing number of organizations have turned to Apache Hadoop to help manage the enormous increase in data while maintaining coherence of the data warehouse, along with data virtualization which provides a single logical data access abstraction layer across multiple data sources enabling rapid delivery of complete information to business users. This paper discusses Apache Hadoop, its

In a recent benchmark conducted on Google Compute Engine, Couchbase Server 3.0 outperformed Cassandra by 6x in resource efficiency and price/performance. The benchmark sustained over 1 million writes per second using only one-sixth as many nodes and one-third as many cores as Cassandra, resulting in 83% lower cost than Cassandra.

Download this special report to guide you through the current landscape of databases to understand the right solution for your needs.

Dresner Advisory Services provides 18 vendor rankings based on user responses about data preparation, usability, scalability, and integration. Among the 18 qualifying vendors, Dell Statistica tied for second place with IBM and SAS. This comprehensive report provides detailed comparisons in an easy-to-read buyers' guide.

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.

About 80% to 90% of the Big Data in large enterprises and administrations is “unstructured” (mostly in natural language) and outside the reach of enterprise applications. To benefit from this “Dark Data”, organizations need the right tools for analysis and value extraction. Such tools must be able to process natural language data, with extremely high performance, while safeguarding access rights. Download this white paper to learn about the advantages of a Real-Time Big Data Search and Analytics solution.

Companies may have approached ETL (extract, transform and load) with a set-it-and-forget-it mentality prior to Big Data, but as some organizations are discovering, that approach needs to change. Download this CITO Research white paper today

In this webinar, Michael Levy, CenturyLink, and Jabez Tan from Structure Research examine the future of the data center and share CenturyLink's predictions on how it will evolve over the next five years and beyond.

It’s clear that digital plays a significant role in shaping how customers engage with brands – but barriers exist that prevent organizations from delivering best-in-class digital experiences to their customers. A recent Forrester Consulting survey of CIOs and CMOs revealed that IT organizations focusing on infrastructure operations and “keeping the lights on” are a barrier to achieving business success, and organizations must collaborate with marketing in order to deliver IT agility. Learn how IT organizations can pivot from infrastructure maintenance to business innovation by downloading this Forrester survey report.

As we become more and more dependent on data to drive our decision-making, the issue of inaccurate, incomplete, or false data poses a major risk. By empowering businesses to inventory, organize, and control information more efficiently, data modeling solutions make governing big data dramatically simpler.

Most enterprises extract data from multiple, and at times conflicting, sources, leading individual business units to view and describe their data in different ways. But at every level throughout a company, informed decision-making depends on the use of properly governed data and information. That’s where data modeling comes in, since an enterprise data model can reconcile the differences in how data is described and presented, and pave the way for a robust data governance program. Are you in complete control of your data? Download this special eBook to learn the key steps to take and the benefits other companies have received by improving their data knowledge and governance.

In this eBook, best-selling author Brian Underdahl explores the fundamentals of data integration and how the latest tools can simplify today’s (and tomorrow’s) data landscape. “Data Integration for Dummies” provides valuable reference if you need to explain data integration to the business, are looking for an alternative to hand-coding data mappings, or simply interested in expanding your knowledge. In five easy-to-read chapters, you’ll discover: • How data and IT infrastructures have evolved • Data integration 101 • Understanding the key technical challenges • See specific examples of how visually oriented data integration tools improve efficiency • Top ten things to look for in a data integration tool

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.

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.

Download the CenturyLink executive brief "Optimizing for Innovation: How Hybrid IT Outsourcing Shifts IT Focus to Innovation” and explore how cost efficiencies can be achieved via the different elements of a Hybrid IT infrastructure outsource approach, allowing IT groups to apply more of the IT budget to innovation.

The right predictive analytics solution can empower you to identify new customers, increase revenue and improve efficiency. View the Hurwitz report to understand why Dell’s Statistica’s enthusiastic customers gave it high marks for value compared to price. Read more to understand why Statistica users are extremely statisfied with the product.

This report examines three-year total cost of ownership differences between IBM DB2 10.5 and Microsoft SQL Server 2014 in representative installations for analytics workloads, showing distinct IBM advantages.

IBM and Oracle have implemented new technologies in their mainstream databases, but there are differences with regard to high-performance analytics and transaction processing. Read the ITG executive brief to see how IBM and Oracle solutions compare in cost and technology.

This white paper is written for SAP customers evaluating their infrastructure choices, discussing database technology evolution and options available. It is not easy to put forth a black-and-white choice as the SAP workloads straddle both real-time analytics and extreme transaction processing, and infrastructure choices can now be vast, given technology advancements around in-memory and faster processing speeds.

This report compares the three-year cost of downtime for mission-critical transaction processing systems for IBM DB2 10.5 and Microsoft SQL Server 2014 showing distinct IBM advantages.

As businesses accumulate increasing volumes of data from their day to day operations, and a wide variety of other sources, transforming that data into actionable information is essential. With today’s data management technologies and techniques no data is beyond integration. IBM DB2 10.5 with BLU acceleration (DB2 BLU Acceleration) takes In-Memory data management and analytics to the next level by optimizing these three key system components: CPU, Memory, and I/O. This holistic approach to optimization is a critical and necessary next step in the evolution of always on, always available, real time data management, analytics, reporting, and OLTP solutions.

You need a database designed to control both the infrastructure and personnel costs that form the IT budget. The next generation of IBM DB2 helps organizations get more value from their big data to improve their IT economics. Major innovations provide out-of-the-box performance gains that go beyond the limitations of in-memory-only systems to support decision making at the speed of business.

In an effort to capitalize on ballooning amounts of data, organizations are placing it in the hands of more users through more channels than ever before. While this enables data-driven decision making and provides better insight into enterprise activity, it also can make sensitive data more vulnerable. Given recent data breaches across multiple organizations, it’s clear that reports, dashboards, and applications containing sensitive information need to be proactively and adequately safeguarded.This paper addresses the critical capabilities needed to secure BI and analytics applications.

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.

According to research by IDC, the digital universe is doubling in size every two years, and by 2020, we will create and copy 44 trillion gigabytes — nearly as many digital bits as there are stars in the universe. So, how can you enable your organization to reap value from Big Data rather than being smothered by it?

Information prowess has become a key differentiator for industry leaders, putting pressure on data professionals. Learn about the three steps to successful collaboration — thinking as one, moving as one, and governing as one — as well as which software can help get your team there.

Discover how collaborative data governance enables organizations to effectively manage IT bureaucracy and drive superior data discovery.

Discover how collaborative data governance allows IT to fulfill its business-data responsibilities while continuously improving users’ data-discovery experience.

The goals of users and IT can sometimes appear to be at odds. Discover how collaborative data governance helps IT deliver better information, faster.

Empower your organizations’ analytical detectives. Learn how the right tools improve the performance and decision making of business intelligence users.

Discover how analytical evangelists build progressive, adaptable organizations and drive collaboration across all levels and functions of business.

Learn how self-service business intelligence (BI) provides gunslinger decision makers with quick and efficient access to data without IT intervention.

Wondering where Oracle’s decision to deprecate Streams leaves you? SharePlex delivers more flexibility and productivity in one affordable solution.

Learn how the proven process outlined in this white paper can help you overcome migration challenges and successfully upgrade to Oracle® database 12c.

Powering real-time applications involves scaling not only existing enterprise applications, but also new applications that have emerged from the web, social media, and mobile devices. Overwhelmed by massive data growth, businesses must carefully select cost-effective technologies that can enable applications to easily manage both the data volumes of today and its exponential growth in the future.

Big data is busting the seams of most enterprise data warehouses. Download this complimentary IDC ExpertROI Spotlight, sponsored by HP, and learn how you can transform your enterprise data warehouse to easily manage and analyze massive volumes of big data without multi-million dollar capacity expansion investment costs.

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.

Workflows are available within Microsoft SharePoint,and help users track and monitor documents or files associated with a specific business process. Although you can use the workflows provided with SharePoint,you can also create custom workflows using .NET. So what options are available and how can you use workflows to benefit your team?

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.

Decision-makers responsible for high-performance OLTP face several considerations as they build their competitive strategy. This paper examines issues of interest to IT leaders responsible for mission-critical data processing.

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.

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.

What is fast data? It's data in motion, and it creates Big Data. But handling it requires a radically different approach. Download the Fast Data Stack white paper from VoltDB. Learn how to build fast data applications with an in-memory solution that’s powerful enough for real-time stateful operations.

Over the last few years, NoSQL database technology has experienced explosive growth and accelerating use by large enterprises for mission critical applications.

This white paper looks at a big data management system, seamlessly integrating Hadoop and NoSQL data, so that big data can become part of business as usual.

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

Oracle Big Data Discovery is designed to be “the visual face of Hadoop” to enable business users to transform raw, big data and mash up with other traditional data into actionable business insight with a single analytics product without programming.

Oracle Big Data Appliance is not just quicker to deploy. It's also cheaper to purchase and operate than the cluster you build yourself. Read this white paper to find out why.

Extract value from your big data and analytics, faster. Read the solution brief from Enterprise Strategy Group and learn how to intelligently stack Dell software, hardware and service offerings to eliminate multi-vendor systems and extract greater value from your investment.

Better decision-making requires requires access to all your data. In this on-demand webcast, the database experts at Dell Software provide tips that can make you an SQL expert — without writing a single line of code.

IT management consultant and information expert John Weathington shares insights to help you succeed as your database environment evolves, including how to improve team provisioning, simplify processes, centralize management and reporting, and implement best practices in the face of constant change.

In this educational webcast, database expert John Weathington will teach you how to get your team thinking, working and governing as an effective unit. With his invaluable advice, you’ll quickly and easily achieve your project goals as part of a highly productive team.

Market Connections, Inc. uncovered the biggest frustrations federal agencies experience in managing data replication, and what they consider to be the most critical replication features. Find out how your agency compares.

Measurement and compliance are the core requirements that all higher-education institutions must pass, and data is the common denominator. Find out how these institutions manage data replication and integration, as well as the features they can’t do without.

This Campus Technology report features highlights from a May 2014 webcast, including survey results from 150 IT decision makers, as well as comments from Dell Software Senior Product Manager Bill Brunt and information on Dell Software's SharePlex data replication solution.

How do you effectively manage and protect your data when it keeps growing at an exponential rate? This Center for Digital Government brief explores the ins and outs of data replication — how it works, what it offers and its appeal to IT professionals.

Using Toad Business Intelligence Suite, Concordia University was able to provide users with a secure self-service mechanism for pulling data that improved visibility and accuracy, as well as saving university staff countless hours annually.

The University of Alaska system needed a tool that would enable both novice and expert users to easily run ad hoc queries against multiple data sources. Find out why they chose Toad Data Point to save time and increase productivity.

This report looks at how higher education institutions are using analytics to recruit and retain the best students, as well as improve the learning experience. Find out how to overcome barriers to implementing analytics across all areas of higher learning.

Find out how schools are using data analytics to personalize the learning experience and improve student outcomes, as well as get tips for surmounting roadblocks to creating successful analytics in your educational setting.

Find out how e-learning company Blackboard more than doubled their number of concurrent users from 36,000 to 100,000 visibility — without any appreciable overhead costs — using Dell™ Foglight for Oracle.

Find out why Miami-Dade County, FL improved services for 2.5 million citizens using Toad software to streamline database administration and development, and why county DBAs are claiming “they just can’t function without it.”

This report compares the three-year cost of downtime for mission-critical transaction processing systems for IBM DB2 10.5 and Microsoft SQL Server 2014 showing distinct IBM advantages.

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.

This case study shows three approaches companies have taken to strategically source SQL Server Development. You can make that strategy even smarter by tapping the proficiency you’ll find through Datavail. As the largest pure play database services company in North America, Datavail explains here how the companies involved were able to reach their strategic goals by easing the burden of developing and implementing optimal solutions for SQL server data management

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.

SQL-on-Hadoop solutions have become very popular recently as companies solve the data access issues with Hadoop or seek a scale-out alternative for traditional relational database management systems. Read this white paper to get a better understanding of the SQL-on-Hadoop landscape and what questions you should ask to identify best solution for your business.

Companies are increasingly recognizing the need to integrate big data into their real-time analytics and operations. For many, though, the path to big data is riddled with challenges - both technical and resource-driven. In this white paper, learn about the concept of the operational data lake, and its potential as an on-ramp to big data by upgrading outdated operational data stores (ODSs).

Ovum, a leading global technology research and advisory firm, discusses Splice Machine's position as the first OLTP SQL database running on Hadoop. Splice Machine turns Hadoop into a SQL OLTP database, fits in the emerging market for distributed Internet-scale transaction-processing platforms, and differentiates from other emerging NewSQL and NoSQL distributed, transaction-processing platforms.

This White Paper introduces you to Splice Machine, the only Hadoop RDBMS on the market. As a full-featured Hadoop RDBMS with ACID transactions, the Splice Machine database helps customers power real-time applications and operational analytics, especially as they approach Big Data scale.

Organizations are now looking for ways to handle exploding data volumes while reducing costs and maintaining performance. Managing large volumes and achieving high levels of concurrency on traditional scale up databases, such as Oracle, often means purchasing expensive scale-up hardware. In this white paper, learn about the different options and benefits of scale out solutions for Oracle database users.

Modern applications need to manage and drive value from fast-moving data streams. Traditional tools like conventional databases are too slow to ingest data, analyze it in real-time, and make decisions. Successfully interacting with fast, streaming data requires a new approach to handling these new data streams.

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.

Philip Howard of Bloor Research compares performance capabilities of the leading business intelligence platforms. Companies studied in this comparison are IBM (Cognos, DB2 with BLU Acceleration), SAP (BusinessObjects, HANA), Oracle (Business Intelligence, Exadata) and Microsoft (Business Intelligence, SQL Server).

Join Dell expert Robert Wijnbelt for this educational session to learn how you can apply real-time and historical performance monitoring to both virtualized and nonvirtualized databases. Get fast, accurate and detailed SQL workload analytics within a flexible monitoring platform.

Are you struggling to manage an increasingly complex database environment? If so, you’re not alone. Research shows that data growth is doubling every 18 months. And it’s not just the massive volume of data you have to manage now. You’re dealing with diverse data types, multiple database platforms, new technologies and the cloud. It’s no wonder most database professionals are reeling just to keep up.

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.

NoSQL databases are seen by many as a more elegant way of managing big, and occasionally small, organizational data. This paper is for technology decision-makers confronting the daunting process of selecting from this fast-growing category of data management technologies. It will introduce a set of comparative features that should be used when selecting a NoSQL technology for your workload and your enterprise. There are many common features across NoSQL databases, but even these have implementation nuances that should be understood.

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".