White Papers

Every modern organization relies on data to operate. And along with that data comes the need to protect, monitor, and use it responsibly. While data discovery solutions offer a range of features, there are some critical points to cover when evaluating one for your own organization. These include: Why you should use a tool for data discovery Key elements of an effective data discovery solution The different data discovery use cases


What does your data quality need? Introducing the Data Quality Maturity Curve Data quality is important—no doubt about it. But like any new data practice, developing a scalable data quality strategy doesn’t happen overnight. And what you need today may not be what you need tomorrow. But where should your team start? Great Expectations? dbt tests? Data Observability? Selecting the right data quality solution for your data platform isn’t about developing the ultimate strategy for forever—it’s about developing the right strategy for right now. In this piece, we examine the Data Quality Maturity Curve—a representation of how data quality works itself out at different stages of your organizational and analytical maturity—to offer some experienced perspective on where you should be right now—and where you’re headed.


Hybrid and multi-cloud computing open new possibilities for data management. The cloud -- whether linked to onsite resources in a hybrid fashion or manifested across multiple services -- offers a cost-effective and responsive approach to managing and making data available to end users and next-generation applications. At the same time, moving to hybrid and multi-cloud data architectures may create new levels of complexity. Download this special report today for key strategies and emerging best practices.


Are you navigating the evolving landscape of database management? Discover how to balance business metrics while efficiently handling complex environments. Learn about the changing role of database management, the rise of multiple databases, and essential features in third-party monitoring tools.


Discover industry expert insights on active-active replication's considerations for achieving high availability. Learn strategies to optimize database uptime and performance critical for business operations.


Unlock insights into the latest trends and benchmarks for cloud adoption and modernization with the 2024 report. Based on a survey of 220 IT and business professionals, it provides valuable insights for organizations.


As data teams shift their approach toward creating reliable data products, they are modernizing their team structure to place data product managers at the helm of these critical business assets. But what exactly does a good product manager do and do you really need one for your team? Our latest eBook answers these questions, diving into important topics such as: Defining the data product manager role and responsibilities What a data product is, types of data products, and how to treat ""data like a product"" The differences and similarities between software and data product managers The importance of basic analytics, AI, statistics, and ML concepts The data product manager career path How to measure success And more! Today, data teams cannot afford to be anything but lockstep with organizational goals. Access this guide today to see how data product managers are integral to establishing and maintaining this alignment.


Securing a Changing Data Landscape One of the most exciting aspects of our data-driven world is its dynamic nature. The data landscape is subject to the constant generation, innovation, and iteration of new ideas from experts and newcomers alike. The most impactful of these ideas are those that take hold across industrial and geographical lines, adopted by and experimented with by organizations. With this in mind, it’s critical that we connect with peers across industries about the trends they are experiencing so we can work together to ensure secure and accessible data use this year and beyond. In our 2024 Trendbook, data leaders share their thoughts on: The growing adoption of distributed architectures like data mesh and data fabric The immediate and long term effects of rapidly evolving artificial intelligence (AI) tools The reprioritization of resources and budgets to revitalize modern data access and data security


As enterprises increase the expanse and range of SQL Server databases via VMware virtual machines, they need to ensure that the data within is protected without disrupting their business operations. While the volume of data and demands for faster data backups and restores grow, IT teams are also tasked with reducing costs to maximize efficiency. This is forcing many to look for ways to consolidate and simplify their infrastructure -- including data protection. Download this special white paper to learn about a new approach to addressing common challenges and ensuring best practices are followed at your organization.


The restrictions and drawbacks of legacy proprietary databases like Oracle have never been clearer—especially in contrast to the freedom and innovation offered by Postgres. As a result, more and more organizations are saying goodbye to Oracle and migrating to greener Postgres pastures—both enterprise and open source. Consistently, those who make this change find themselves with more flexibility, better control of their data and an enhanced ability to modernize. In this eBook, you’ll learn about the experience of three such businesses: a remote telemetry leader that reduced licensing costs and accelerated customer experiences a telecommunications business support provider that harnessed Postgres for agile and cost-efficient application modernization an automotive repair juggernaut who underwent a major transformation project without the fear of vendor lock-in or excessive downtime How can Oracle migration empower you? Let’s find out.


This white paper focuses on the most popular source and target for database migrations: moving from Oracle to Postgres. Oracle is the #1 legacy database, and its extremely onerous license policies are driving the majority of migration demand. Postgres is the logical target for the migrations. With a constant stream of innovations reflected in annual releases, Postgres has achieved three major database of the year awards from DBengines.com, recognition as the #1 database in StackOverflow’s annual developer survey, and the position of #1 database on the Cloud Native Computing Foundation’s tech radar. Not only is it clear that Postgres is winning the hearts and minds of innovation drivers, but its small footprint makes it an ideal solution in containers too (see Datadog survey). The principles and approaches described in this paper are applicable to other source/target combinations as well. You’ll find: A quick review of the business drivers and migration approaches; A dive in


Given today’s economic uncertainty, many organizations are taking a closer look at their budgets. Lowering the total cost of ownership (TCO) factors into every decision companies make. See how three leading organizations today are escaping legacy databases and using EDB’s migration tools and support to break free from restrictive legacy databases, increase performance, accelerate innovation, and decrease TCO.


Today’s financial service providers are under pressure from multiple angles. Increased customer expectations, growing digitization, expanding data volumes, regulation complexity, security threats, rising costs, and competitive challenges are requiring banking, financial services, and insurance (BFSI) organizations to modernize and future-proof their technology. Business leaders are constantly searching for ways to minimize expenses and optimize the total cost of ownership (TCO) of their technology. One way is by taking a good hard look at their database and database software. This eBook walks through how CIOs and CTOs are successfully decreasing TCO via ensuring their database technology is running at optimal levels, avoiding hidden costs and keeping pace with digital transformation. Read this eBook to learn how EDB customers ensured their user experience and improved their database availability, flexibility, reliability and security with Postgres.


This document presents a framework and a series of recommendations to secure and protect a Postgres database. We discuss a layered security model that addresses physical security, network security, host access control, database access management and data encryption. While all of these aspects are equally important, the document focuses on Postgres-specific aspects of securing the database and the data. For our discussion of the specific security aspects relating to the database and the data managed in the database, we use an AAA (Authentication, Authorization and Auditing) approach common to computer and network security. Most of the recommendations in this document are applicable to PostgreSQL (the Community edition) and to EDB Postgres™ Advanced Server (EPAS), the enterprise-class, feature-rich commercial distribution of Postgres from EnterpriseDB® (EDB™). EPAS provides additional relevant security enhancements such as Transparent Data Encryption, password profiles, auditing, data


Today’s financial service providers are under pressure from multiple angles. Increased customer expectations, growing digitization, expanding data volumes, regulation complexity, security threats, rising costs, and competitive challenges are requiring banking, financial services, and insurance (BFSI) organizations to modernize and future-proof their technology. Read this eBook to learn how EDB customers ensured their user experience and improved their database availability, flexibility, reliability and security with Postgres.


In today’s rapidly evolving, data-driven world, C-level executives in banking, financial services, and insurance (BFSI) are under tremendous pressure to ensure their database systems are operating as they should be. Download this eBook to discover how database stability and resiliency are helping CIOs overcome their challenges and sleep more soundly.


The banking and financial services (BFSI) industry has entered a new era spearheaded by disruptive, tech-savvy, and well-funded fintechs, expanding the boundaries of open banking. This is why a growing number of BFSI companies are turning to open source technologies. Open source databases, such as Postgres, offer the greatest flexibility in how enterprises unlock the power of data. In this guide, we’ll explore why open source is such a good fit for BFSI organizations that are committed to digital transformation, and outline the key factors that can ensure your success.


For real time streaming and queuing technology, Apache Kafka® is truly unrivaled, but it can be an inscrutable beast for newcomers. Without proper guidance, it’s easy to miss out on Kafka’s full capabilities. While not the easiest technology to optimize, Kafka rewards those willing to explore its depths. Under the hood, it is an elegant system for stream processing, event sourcing, and data integration. In this white paper, we cover the 10 critical rules that will help you optimize your Kafka system and unlock its full potential.


There are a number of reasons you may be looking to migrate from DataStax Enterprise (DSE) to open source Apache Cassandra®. Perhaps you want to cut costs or eliminate vendor lock-in, or you feel excited about participating in the vibrant open source community. No matter your reason for making the change, we’re confident you’ll find Apache Cassandra to be a powerful replacement for DataStax Enterprise and that it will provide you with maximal value over the long term. This document is a guide for migrating from DataStax Enterprise to Instaclustr Managed Cassandra. It’s intended for solutions architects, engineers, IT Directors, or others on the front lines of planning and executing the migration. Throughout this material, we will go over different considerations to bear in mind for planning an effective migration with zero downtime.


The open source movement has taken center stage in software development, and its influence echoes through other areas of life such as open culture and open data. Many software companies hope to cement both their revenue sources and their status in open source communities by offering a mixture of open source (also called free) and closed (proprietary) software. The combination is generally called open core.


With its impressive capabilities and evolving technology, there is a good reason why Apache Cassandra® continues to be a popular database choice for companies of all sizes. In this Instaclustr white paper, discover its common use cases and how to best avoid any pitfalls.


Ensuring that data is readily available, secure, and accessible to data scientists, data applications, and other stakeholders across the enterprise is no easy task. In today’s organizations, data engineers wear many hats and the role continues to grow in importance. Download this special report for an overview of the top trends, challenges, and opportunities moving forward.


When it comes to building data and AI platforms at scale, few companies work at the scale and speed of personal finance application Intuit CreditKarma. Vishnu Ram, VP of Data Science & Engineering at CreditKarma, joins us to walk through how his team designed and implemented their modern data and AI platform to power 35B financial predictions daily for over 120 million members. He’ll discuss the technologies, processes, and team structure required to build a data, ML, and AI function from scratch, and the role of data observability in this equation.


The Forrester Wave™: for Streaming Data Platforms, Q4 2023 is a key source of information for any organization looking to deploy real-time applications that deliver instant action on streaming data. In this report, you get a comprehensive view of the most significant streaming data platforms in the market today and their respective strengths. In this report, Forrester evaluated 14 vendors and reviewed them against 21 different criteria related to a company’s current offering, strategy, and market presence. Hazelcast was evaluated as a Strong Performer in this report and received the top scores possible in the following criteria: Throughput Enrichment Latency Vision Innovation Roadmap Why the Wave Matters Streaming data is becoming a priority for enterprises with real-time aspirations and the goal to use it as a competitive advantage. It’s not only a snapshot of what is happening across the business, streaming data opens new possibilities for real-time applications tha


Many businesses are already taking advantage of real-time data. But the challenge today is that they are predominantly focusing on faster access to stored data, and thus not on taking faster action when data is created, and when opportunities arise. Many “streaming” technologies today must first store data and then rely on humans to gain insights via manual analysis and then respond in human time. A complementary approach that leverages stream processing engines will address business problems that need immediate, automated responses. This paper covers: Leveraging stream processing technologies to respond in real-time for use cases like “right offer at the right time” (i.e., real-time offers) and transaction fraud detection. Using real-time data to drive better business outcomes via recommendations or reduced loss from fraud. How to better identify the real-time use cases that you can deploy to gain competitive advantage. Register now to get your digital copy of this free ebo


Instead of a feature-by-feature comparison between these two popular technologies, there is a more meaningful way to determine which is right for you. After all, comparing Hazelcast to Redis is almost like comparing a sports utility vehicle (SUV) to a pickup truck. Picking one of these vehicles over the other depends on how you plan on using them. It’s the same with Hazelcast versus Redis. The main difference between Hazelcast and Redis is that as a unified real-time data platform, Hazelcast provides stream processing capabilities that you don’t get in Redis. So if you are looking to take instant action on real-time data, in which your applications help you respond to changes in data when it matters most, Hazelcast is your technology. Read this paper to learn how Hazelcast covers all your bases for your stream processing needs, and hopefully, you won’t need to spend so much time figuring out how to differentiate Hazelcast from Redis or any other storage-only data platforms.


Modern data architectures require real-time capabilities that will support the emerging AI-infused enterprise. Download this special report for the latest best practices and emerging technologies to keep in mind on your journey.


Leading global organizations like J.B. Hunt and Swedbank have long relied on Databricks to unlock deep insights and power their data and AI workloads. The arrival of Databricks Unity Catalog broadened this scope by providing unified governance for data and AI assets, which is essential as data usage, regulations, and threats continue to grow.


To deliver trusted data and harness a broad range of data sources, organizations require an advanced data management platform that’s easy to use and cost-effective.


According to McKinsey, generative AI and other technologies have the potential to automate work activities that absorb 60% to 70% of employees’ time. Work smarter with generative AI-powered iPaaS and transform the way you design, test, deploy, manage and scale your workflows.


The value of cloud data pipelines is clear: They help enterprises build analytics quickly, automate ingestion and data processing workflows and more. However, pinpointing the right data pipeline solution — one that supports complex use cases and incorporates generative AI — is another story.


According to Gartner, “Poor data quality destroys business value. Recent research shows organizations estimate the average cost of poor data quality at $10.8 million per year.”


Take a modern approach to data integration with the right data integration solution that can help unify, govern and share data. Get started with the 2023 Gartner® Magic Quadrant™ for Data Integration Tools. In fact, Informatica has been named a Leader — placed highest in Ability to Execute and furthest in Completeness of Vision for 10 years straight.


Currently, 97.2% of organizations invest in big data and artificial intelligence (AI). In addition, the generative AI (genAI) market is poised to explode, growing to $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022.


The sports industry has seen a significant rise in the adoption of data and analytics to gain a competitive advantage and improve the fan experience. The Texas Rangers are at the forefront of this movement, as they analyze terabytes of in-game data to optimize player performance and scouting. Join this webinar to learn how the Rangers’ data team overcame the challenges of technical resource constraints and the complexities of scaling real-time data pipelines with Prophecy’s low-code data engineering platform.


Software license compliance audits are a big business for enterprise vendors -- and they're on the rise right now. Now is not the time to ignore the risk of a potential audit of your organization. This survival guide will help you understand Oracle’s audit process and navigate through it when they come knocking.


Security, agility, and visibility – how are data leaders prioritizing these initiatives to protect and strengthen their businesses in 2024? Generative AI has opened up a vast new world of productivity, possibility, and most critically, risk. AI models and use cases are being built, deployed, and restructured within a span of just months. The rate of technological innovation has left many data leaders weighing the balance between substantial gains and frightening setbacks. In an effort to develop an authentic understanding of the current moment, we surveyed 700+ data platform and security leaders who are asking today’s most pressing questions: How should I allocate my tech and human resources to optimize our data security? How can I improve my data team reporting structure? How are others navigating organizational, technological, and process-level security risks? How can my actions as a data leader directly drive better business outcomes? What pressing needs and data security p


There is a growing disconnect between enterprises seeking greater data-driven capabilities and the actual data that is on the ground of their business units. That’s because bottlenecks, silos, over-centralization, and organizational layers are hindering the access and capabilities needed by rapidly expanding userbases. Download this special report for best practices associated with successful data mesh design and development.


Don't venture into a data-driven world without data preparation. This white paper reveals the game-changing role of data prep. Get ready to harness data's true power for smarter, more informed decisions.


Discover the power of enterprise data modeling. This white paper reveals how it drives business value and lays the foundation for effective governance. Unearth insights on how to optimize data for your organization's success.


Explore the future of intelligence with this IDC analyst report. It's a roadmap to data intelligence, dissecting its vital role in shaping tomorrow's strategies. Dive in for insights that matter to your data-driven future.


Unlock the full potential of your data with this eBook. It's your guide to unleashing the true value hidden within your data assets. Dive in to make your data work harder for your business.


Get ready to revolutionize your database development game. This eBook is your ticket to an agile approach that spells efficiency and innovation. Uncover the keys to adapt, optimize, and keep your data projects agile.


Dive into the world of high availability with our white paper. It's your guide to understanding active-active replication essentials. Learn the strategies and insights that keep your systems ticking without missing a beat.


Unlock the potential of cloud operations with this resource. Discover why data empowerment is the linchpin to success. Explore insights that transcend traditional boundaries and learn how to harness the true power of your data.


Get expert guidance on optimizing your PostgreSQL spend. This white paper outlines strategies to control costs through improved infrastructure efficiency, operations automation, smart cloud utilization, vendor management, and more.


As MySQL usage grows, infrastructure and operations costs can spiral out of control. This guide explores strategies to assess expenses, tune configurations, evaluate cloud pricing models, optimize infrastructure, leverage caching, and maximize your database investments.


If ever there was a list of ‘nightmare scenarios’ that every business owner would agree upon, very near the top of that list would certainly be ‘irrecoverable data loss.’ While many prudent companies have detailed business continuity plans and standard operating procedures in place to minimize the impact when something bad eventually does occur, for whatever reason, others simply do not— leading to a nightmare scenario. In this white paper, Instaclustr Professional Services Consultant Perry Clark recounts a true story about such a scenario, and how he and his team was able to overcome the daunting challenges presented.


Instaclustr PostgreSQL® on Azure NetApp Files (ANF) is up to 325% faster (TPS) and 70% cheaper ($/TPS) than equivalent Instaclustr Managed PostgreSQL instances using Azure Premium Disk. Using the higher IOPS available on ANF storage we can increase read/ write transactions per second (TPS) by 135% to 167% and read-only by 193% to 325% vs an Azure Premium Disk based Instaclustr PostgreSQL. Using ANF provides a 50%+ reduction in the cost per TPS performance of heavy read/write workloads on a PostgreSQL database.


Growing in popularity in recent years, data mesh architectures promise a wide range of benefits for modern organizations: increased data democratization, elimination of data silos, and the enablement of more widespread, business-driving data access and use. In practice, however, operationalizing a scalable and secure data mesh can be a complicated process. With the right practices, platforms, and people, modern organizations can achieve a data mesh implementation that meets their needs without compromising speed or security. In this eBook, you’ll learn: What a data mesh is and what benefits teams have come to expect The complexity of data mesh security, including common challenges 3 key steps to achieving a secure data mesh implementation How the Roche team is achieving results with data mesh


In the face of increasing demands for speed and adaptability, the challenge of maintaining the performance and availability of critical systems and applications is intensifying. To accommodate the realities of modern data and applications -- highly distributed, modular, portable -- new technologies and strategies are essential. Download this special report to stay ahead of the curve when it comes to database performance.


Learn how your organization can utilize the iterative approaches that might already be in place for product development and project management to build more effective and transparent Data Governance initiatives.


Responsible data use should be high on the agenda of any organization. From transparency to security and beyond, handling data responsibly is a central consideration for developing consumer trust and ensuring you are doing right by your customers. Download this infographic to learn more about the six guiding principles for data responsibility and why it is crucial that you follow them.


Data is your organization’s most valuable asset. But without a governance program in place, it can quickly become a liability. This guide covers all the steps needed to build a data governance strategy and program, including: How to establish a data governance framework Steps to discover, classify, and understand your data Ways to implement technical controls that support governance policies Tips to manage and monitor your program performance


Modern master data management (MDM) is essential for success — it serves as a hub for consolidating trusted data, automating data quality and bridging the gap in data fabric architecture.


In today’s digital economy, data is your most strategic asset. Yet organizations continue to struggle with disparate, duplicate and conflicting information from a wide range of data sources across the enterprise. In fact, 55% of data leaders reported they have more than 1,000 sources of data in their organization.


Don’t underestimate the value of artificial intelligence (AI), machine learning (ML) and data science. What once used to be figments of the imagination (like facial recognition, smartphones and driverless cars) are now reality.


Organizations are struggling to achieve data-driven business transformation because their data, applications and processes are disconnected. In today’s competitive, digital-first economy, it’s critical to reimagine your integration strategy with a modern integration platform-as-a-service (iPaaS) solution.


The term sounds impressive when you say it, and a lot of industry analysts extol its virtues, but what does it take to become part of a modern analytics ecosystem? Unlike installing an application or populating a data warehouse, becoming part of an analytics ecosystem involves many moving parts across not only your own enterprise, but others as well. Download this special report key considerations to get started.


From legacy infrastructures to public clouds, the average enterprise has data spread across different locations, file systems, databases, and applications—and the volume and sources of that data is constantly growing. As a result, while most organizations want rapid access to meaningful, actionable information, effectively integrating and governing data is becoming more difficult. Download this special report for best practices in developing a forward-looking data integration and governance strategy.


Business-critical applications have very strict requirements when it comes to availability, performance, recoverability, scalability, and security -- and Oracle shops are no exception. An important step in successfully modernizing these applications is finding the right cloud that matches your requirements. The ability to mix and match providers without code or configuration changes through a consistent multi-cloud infrastructure offers significant advantages. Watch this special podcast to learn how you can rapidly migrate Oracle workloads to VMware Hybrid Multi-Clouds with license compliance.


Unlock the potential of practical enterprise architecture and data modeling. Explore a white paper that guides you through essential steps to effectively gather, connect, and share data for strategic advantage.


Unleash your enterprise data's value with metadata management. Explore a white paper that reveals the transformative role of metadata in driving data-driven decisions and strategic growth.


Elevate your open-source database management with Toad Edge. Uncover strategic insights that empower efficient performance, streamlined operations, and informed decision-making in a dynamic digital landscape.


Gain insights from migration experts on successful database transitions. Uncover the five key considerations essential for a seamless migration, ensuring your transition to Postgres is optimized for success.


Navigate database modernization choices with expert insights. Uncover the optimal path—rehosting, replatforming, or refactoring—aligning with your goals. Elevate efficiency, scalability, and performance for sustained success.


Unlock the power of PostgreSQL for enterprise success. Explore a comprehensive resource that offers strategic insights, enabling you to harness the full potential of this versatile database solution.


Elevate your security with essential insights. Navigate the evolving landscape confidently, ensuring robust protection. Equip yourself with knowledge that safeguards your digital endeavors effectively.


Uncover the vital link between database performance and business success. Gain insights into optimizing efficiency, enhancing user experiences, and achieving unparalleled growth through the strategic management of databases.


Discover invaluable insights on overcoming universal obstacles. Uncover hidden solutions, fostering expertise that transcends limitations. Propel your understanding to new heights and conquer challenges with confidence.


Unlock the potential of hybrid and multi-cloud strategies using SharePlex by Quest Software. Optimize data movement for seamless cloud integration and gain a competitive edge.


Explore proven techniques for seamless Oracle database migration to the cloud. Gain insights into challenges, strategies, and benefits for a successful transition.


As organizations grapple with ever-expanding amounts of data, they need to find ways to manage, integrate, and analyze information across their tech stack. There are two main approaches to meeting this challenge: data integration (ETL/ELT) and data virtualization (DV). Explore which solution fits your data needs, and how combining both just might be the answer.


In many organizations, data not only defines what the business is, it is the lifeblood of how business operates. Yet data is a largely intangible and invisible thing, residing in locations that most of its users never see, appearing on the network when summoned over unwired connections, delivering the information necessary for applications to run, and returning to be managed and protected while remaining available for future use. How natural it all has become. And how critical it is that everything goes off without a hitch. Who makes it happen, this tangible use of intangible data? What, exactly, do they do? And how do they get to the point where an organization will entrust them with the care and feeding of its valuable data assets? This whitepaper is written by IDERA, a global leader in database management software, to provide insight into the position of database administrator (DBA) for readers who are new to the DBA position or who want to expand their capabilities as one of


Every enterprise is seeking a real-time analytics solution to power their decisions, but how do you choose the right one for your business? Airbnb asked this same question before identifying StarRocks as the right choice for their real-time trust analysis, Tableau BI reporting, metrics management, and more.


The demand for low-latency, high-concurrency analytics solutions has given rise to offerings touting capabilities like columnar formats and denormalized tables. While these options improve performance, they come with tradeoffs. How do you choose the right one? Sanjmo examines one popular solution, StarRocks, a new offering overcoming many of these challenges.


The logical data management space is not new, with many established technologies and new product categories. In this whitepaper, we will explore the strengths and limitations of three popular approaches to integrating and managing distributed data to help you make an informed decision.


Cloud data warehouse, data lakehouse, data fabric, data mesh? And what about real-time analytics and streaming IoT data? Right now, IT leaders and data architects have a plethora of architecture patterns and enabling technologies to consider when evaluating strategies for modernizing their data infrastructure.


From the adoption of hybrid and multi-cloud architectures to ongoing advancements in machine learning, automation and security, the world of database management continues to evolve. Download this special report for key enabling technologies and evolving best practices today.


It only seems like yesterday that batch processing was the norm. Now, decision makers want almost instantaneous glimpses of their business and its performance—and the tools that enable such capabilities. There are many data management strategies and tools for achieving real-time capabilities. Download this special report to dive into the key approaches and technologies to succeed.


Building an application that can scale isn’t easy. Efficiently building an application that can scale globally is even harder. O’Reilly’s new Architecting Distributed Transactional Applications report takes an in-depth look at the best way to build modern applications, taking into account practical considerations such as efficiency and affordability. The final report offers a practical guide to designing modern application infrastructure, and walks readers through the advantages and disadvantages of the popular platforms and deployment methods they'll need to assess as part of the process. It offers a blueprint for building modern, distributed, transactional applications that offer blazing-fast performance and ironclad resilience while minimizing spend (in terms of both dollars and engineering hours). It is, in other words, the recipe for building an efficient, modern, global application.


In these complimentary chapters from O’Reilly, you will explore the essential ingredients of designing scalable solutions, including replication, state management, load balancing, and caching. Ultimately, you’ll learn the design principles and key concepts of distributed systems including: Scalability and architecture trade-offs Scaling out the database with caching Distributed the database Consensus in distributed systems Time in distributed systems


Download a free copy of O’Reilly’s CockroachDB: The Definitive Guide. Whether building from scratch or rearchitecting an existing app, modern distributed applications need a distributed database. This essential reference guide to CockroachDB — the world’s most evolved distributed SQL database — shows how to architect apps for effortless scale, bulletproof resilience, and low-latency performance for users anywhere.


In today's data-driven world, high availability is crucial for Oracle and PostgreSQL databases. Watch this informative video to understand the significance of ensuring data availability, minimizing downtime, and enhancing the resilience of your critical database systems. Gain insights into industry best practices and learn about various strategies and technologies that can help you achieve high availability for your Oracle and PostgreSQL databases. Explore real-world examples and discover how organizations address the pain points associated with database downtime and data unavailability. Elevate your database management skills and implement robust high availability solutions to safeguard your data and keep your systems running smoothly.


If you're wondering whether data modeling is still relevant in today's fast-paced, data-driven world, this white paper is for you. You'll discover how data modeling can help you overcome challenges and achieve success in your database-related role. You'll learn why it's still an essential component of modern-day data management strategies, helping you reduce errors and increase efficiency. The paper also covers key concepts and best practices, helping you create better models that more accurately represent your data. Ultimately, this white paper is a must-read for anyone looking to understand the critical role data modeling plays in data management and governance.


Selecting the right data modeling solution can make a significant impact on an organization's database management practices. In this white paper, you'll learn about the top 10 considerations to keep in mind when making this decision. From evaluating modeling capabilities to assessing vendor support and data governance features, this resource will provide you with the information you need to make informed choices. Whether you're just starting your database journey or looking to switch to a new provider, this white paper will offer valuable insights on selecting a data modeling solution that aligns with your organization's unique requirements and goals.


Are you struggling to get a handle on your NoSQL databases? Are you concerned about the security, performance, and scalability of your data infrastructure? Then you need to read "Taking Control of NoSQL Databases," an informative eBook from erwin. This resource will teach you everything you need to know about NoSQL databases, including the pros and cons of various types of NoSQL databases, the challenges of NoSQL data modeling and schema design, and best practices for securing and optimizing your NoSQL databases. With this eBook, you'll be able to take control of your NoSQL databases and avoid common pitfalls, ensuring that your data infrastructure is secure, scalable, and performing at its best.


In today's ever-changing business landscape, it's essential to have the relevant insights to weather any crisis. This white paper explores how data catalogs can ensure your organization is prepared for the unexpected. You'll learn how data governance preparedness can help mitigate risks, ensure compliance, and foster a culture of data-driven decision-making. Discover the benefits of automating the data cataloging process, such as improved data discoverability, lineage tracking, and data quality. With data catalogs, you can gain a holistic view of your data assets, making it easier to identify critical data elements and mitigate potential data breaches. Don't wait until it's too late; read this white paper to prepare your organization for any crisis.


If you're looking to stay ahead in the world of operations, this IDC Analyst Perspective report is a must-read. You'll gain expert insights into controlling data in the future of operations and learn about best practices for database management. The report covers key topics such as data intelligence, data governance, and data privacy, and provides a clear view of the future of data management. Whether you're a data analyst, database administrator, or IT professional, you'll benefit from this report's guidance on how to future-proof your skills and succeed in the rapidly evolving landscape of data management.


Gain insights into the current state of data governance and empowerment with our 2022 report infographic. Learn about key trends and statistics in the industry.


Gain valuable insights into the current state of data governance and the impact of data intelligence and automation on organizations with the 2022 State of Data Governance and Empowerment Report. This report provides data and analysis on data governance trends, challenges, and best practices, along with actionable recommendations to improve data management and enable data-driven decision-making. Learn how organizations are leveraging data governance to drive innovation, reduce risk, and improve operational efficiency, and get insights into the role of technology and automation in supporting these efforts. This report is essential reading for anyone looking to optimize their data governance strategy and empower their organization with data.


This technical brief is essential for database developers and DBAs who are responsible for SQL Server DevOps CI/CD pipelines. By reading this asset, viewers will learn how to optimize their pipelines for speed and security, using automation and monitoring tools. This will result in faster delivery of database changes, while reducing the risk of errors and breaches. The brief offers practical guidance on topics such as continuous integration, continuous delivery, database deployment automation, and source control. By following the advice presented in this asset, viewers will be better equipped to deliver high-quality software in less time, with fewer errors and security risks.


Preparing data for analysis is often a time-consuming and frustrating task, but it's a necessary step for gaining insights and making informed decisions. In this e-book, you'll learn about the four most common roadblocks to data preparation and how to overcome them using data modeling techniques. From understanding data sources to identifying relationships and dependencies, this e-book provides best practices and expert tips for making data preparation a more efficient and effective process. Whether you're a data analyst, data scientist, or database administrator, this e-book will provide you with valuable insights to help you get the most value from your data.


Discover the ESG-validated insights that propel IT excellence. Uncover how Foglight elevates performance monitoring, ensuring optimal operations and empowering your organization with data-driven decisions.


Are you feeling overwhelmed and lost in the rapidly evolving database world? Fear not, this e-book is here to help. Using an entertaining zombie apocalypse analogy, you'll learn how to avoid becoming a "database zombie" and instead thrive in your career. The book covers topics such as the impact of emerging technologies, the importance of collaboration between teams, and how to stay ahead of the curve in your skillset. Whether you're a seasoned database professional or just starting out, this guide is a must-read for anyone looking to survive and thrive in the changing world of databases.


Downtime can be disastrous for businesses, particularly when it comes to databases. Learn why databases are critical to businesses and how database downtime can adversely affect them in this informative infographic. Discover the cost of database downtime, including financial costs and damage to business reputation, and the steps you can take to minimize it. Whether you're a database administrator, IT manager, or business owner, this infographic provides valuable insights on how to keep your databases up and running smoothly. With real-world statistics and practical tips, you can ensure that downtime is for vacations, not databases.


Kubernetes is the definitive choice for container orchestration. Cassandra is the gold standard for open source NoSQL. Put them together and you’ve got the cloud-native app dev stack that dreams are made of—as long as you can keep complexity from creeping in. That’s where tools like K8ssandra, Cass Operator, and Stargate come in. Read this ebook to discover the flexibility of Kubernetes for multi-cloud deployments and how you can: Abstract away the complexities of deploying Cassandra on Kubernetes Grow, run, and manage your Cassandra environment with ease Avoid vendor lock-in: deploy on any cloud or multiple clouds including AWS, GCP or Microsoft Azure


Companies need a fast, flexible way to deliver applications—and traditional app dev approaches just can’t keep up. To gain insight into the cloud-native strategies transforming modern business, ESG surveyed 387 IT professionals responsible for evaluating, purchasing, managing, and building application infrastructure, and discovered that: 73% of organizations are currently developing cloud-native applications based on microservices architecture Nearly 9 in 10 organizations currently deploy production applications and server workloads on public cloud infrastructure and/or platform services 60% of respondents agree that cloud-native application deployment and delivery provide a faster time to value than traditional apps Find out how microservices, APIs, Kubernetes, and serverless data are redefining application development for a new era of business. Get the survey results and accelerate time to market with cloud native development!


A web API can connect cloud apps with databases with less friction than native drivers—but which one? To deliver the right balance of productivity and performance for each app, developers need the flexibility to use any HTTP API they choose. That’s where an API gateway comes in. Read this ebook to learn how an API gateway allows you to use any native driver or open source API you choose—from CQL API and REST API to gRPC API—so you can: Connect apps to databases easily regardless of data model or schema design Focus on writing business services instead of translating query languages Build real-time apps with Cassandra with the API of your choice using Stargate is also available via DataStax Astra DB, the serverless database built on Apache Cassandra. Together, these essential pieces of data infrastructure are key to shortening that critical path to getting an application to production.


Databases contain valuable business assets; ensuring this information is secure is paramount. SQL Compliance Manager by Idera can protect those assets and help address your industry’s strict regulatory compliance requirements with confidence, providing HIPAA-compliance, GDPR-compliance, and more. According to IBM, 2022 was the 12th year in a row that the United States paid the highest cost for a data breach, with $5.09 million more than the global average. The average cost of a data breach is $9.44 million in America, and the healthcare sector continues to be impacted the most.


The digital era now upon us calls for new approaches to data governance and security. Download this special report for best practices to design and develop data governance and security for a modern data ecosystem.


In-memory caching plays an important role in overcoming data fragmentation and network latency challenges related to distributed microservices architectures. This paper covers the advantages of microservices, the need for performance optimization, high availability, and how a cache-based messaging layer facilitates inter-microservice communication.


Data fabric is a term used to describe a set of technologies, services, and strategies that provide ‘a unified and reliable view’ of data spanning hybrid and multi-cloud environments. Eliminating data silos, surfacing insights more effectively, and increasing the productivity and value of data are some of the ways data fabric can improve data management at organizations. Download this special report to dive into building a data fabric, including key components, challenges, and emerging best practices.


The world of databases is undergoing a major transformation with the explosion of data and shift to cloud services. AWS is helping companies modernize their data architecture to increase innovation and business agility. This whitepaper explores the modernization strategies, considerations, and best practices of migrating Oracle Exadata workloads to AWS.


Servers, virtual environments, laptops, tablets, smartphones, IoT devices—the average organization has more endpoints than ever before, especially as hybrid work and the use of cloud computing have skyrocketed. This makes defending against ongoing security and compliance risks a real challenge. Stephen talks with Joe McKendrick and Jody Evans on the current state and evolution of endpoint management.


Companies may consider encryption or anonymization to protect sensitive cloud data like PII and PHI, but download this eBook to learn why tokenization is the more secure and flexible solution for cloud data security. And learn 3 risk-based models for integrating tokenization to keep your sensitive data migration safe.


Traditionally, data modeling produces a set of structures for a Relational Database Management System (RDBMS). First, we build the Conceptual Data Model (CDM) to capture the common business language for the initiative (e.g., “What’s a Customer?”). Next, we create the Logical Data Model (LDM) using the CDM’s common business language to precisely define the business requirements (e.g., “I need to see the customer’s name and address on this report.”). Finally, in the Physical Data Model (PDM), we design these business requirements specific for a particular technology such as Oracle, Teradata, or SQL Server (e.g. “Customer Last Name is a variable length not null field with a non unique index...”). Our PDM represents the RDBMS design for an application. We then generate the Data Definition Language (DDL) from the PDM, which we can run within a RDBMS environment to create the set of tables that will store the application’s data. To summarize, we go from common business language to business r


This Enterprise Software Solution Provider (ESSP) has been an Oracle® customer for over a decade. ESSP was audited by Oracle and found in violation of their license agreement. Unfortunately, some database features, Diagnostics and Tuning Pack, that ESSP did not use — and was not paying for — were accidentally turned on. ESSP owed Oracle $200k for unpaid license fees, which was 300 percent more than their existing Oracle annual spend.


“Most of an organization’s data is unstructured and held in tools with open access to employees. Unlike structured data stored in databases which can more easily be governed, file storage systems, business messaging systems, and email increases risk of data loss, financial damage, and reputation risks for businesses. Download this infographic to learn: The differences between unstructured and structured data How to track risky data A three-pronged approach for de-risking sensitive data”


“This explosion of data is putting tons of pressure on IT and security teams to know and keep track of all their data so they can secure, monitor, and de-risk that digital information In this infographic, you’ll learn about: Evolution of data friction Identifying pressure points Where data actually resides Download for a quick look at how to gain visibility and take action in de-risking your data.”


Data security is considered a must-have for modern organizations that want to compete with data while avoiding regulatory penalties. But implementing data security measures often comes at the expense of fast, efficient data access. In an increasingly complex and decentralized data environment, how can organizations strike the balance between security and utility? Data Security for Dummies helps for solve this dilemma, with expert guidance on: The key facets of a data security strategy, including data discovery, access control, and monitoring for threat detection Who should be involved in making data security decisions and executing controls How to build an access control framework and why attribute- and purpose-based controls are the key for scalability 10 real life scenarios in which organizations both big and small leveraged data security and access control to drive business results


In this whitepaper, you will learn from Mike Ferguson, an industry expert and the Managing Director of Intelligent Business Strategies, about what makes up a data mesh. The whitepaper talks about the critical capabilities of data mesh as an architectural concept and how these lead to successful data and analytics within any organization. Mike also delves into the role of data virtualisation in a data mesh, and how data virtualisation and data catalogues help organisations find business-ready products in their data mesh implementations. Finally, Mike will share his thoughts on how data virtualisation supports robust data governance within a data mesh implementation.


Nearly 60% of organizations have gained a competitive advantage from data lake initiatives and nearly half have realized improved customer experience. In addition, best-in-class organizations with data lakes in place are seeing improvements in their bottom line, with 71% reducing IT costs for storage and data management.


According to a 2023 data engineering market study (conducted by Dresner Advisory Services), Informatica ranks as the #1 top vendor.


With economic pressures and tighter budgets, it’s important to make the right investments with the most value. When vetting any new vendor or solution, you want to know exactly what you’re going to get in return.


According to a CIO.com survey, the number-two top tech initiative driving IT investments in 2022 was data/business analytics. This isn’t surprising given trusted and secure data analytics comes with several benefits: faster productivity and business growth, lower costs and smarter data management.


An IDC report found that 95% of CEOs see the need to adopt a digital-first strategy. If you’re a data leader, this means you’re on the hook to create an innovative IT strategy and enterprise architecture that can thrive in today's high-pressure, digital economy.


To navigate today’s rapidly changing business landscape, enterprises need to maximize the value of their data to drive efficiency, agility, and innovation. From accelerating analytics, artificial intelligence (AI), and machine learning projects to supporting next-generation data fabric architectures, knowledge graphs have emerged as a powerful solution for enterprises hungry for greater automation and intelligence. Download this special report to get a deeper understanding of the key strategies, emerging best practices, and new technologies.


As organizations seek to design, build, and implement data and analytics capabilities, they are pressed to reinvent and reorient their data architectures—as well as justify these activities with ROI measures. From the cloud-native data warehouse and data lakehouse to data mesh and data fabric, a range of architecture patterns and enabling technologies have come to the forefront of modernization discussions. Likewise, many organizations right now are eyeing new strategies and solutions to enable more agile and responsive data and analytics systems. Ultimately, moving to a next-generation architecture is a journey; not a sprint. Download this special report for key considerations to succeed along the way.


A recent report shows a 149% increase in fraud attempts targeting financial services, and credit unions are no exception. Is your credit union constantly trying to keep up with fast-changing threats only for new tactics to make your security solutions obsolete? Discover five critical capabilities you should understand to ensure your fraud solution closes security gaps and the role complementary technologies can play. Download this white paper and learn about: The 5 most important capabilities of fraud solutions for credit unions today How geolocation data can uncover fraudsters and enrich existing data Streamlining and improving document verification accuracy And more!


Up to 20% of contact data entered contains errors. But do you know what the long-term costs of working with bad data are? This whitepaper explains the 1-10-100 rule, and how it illustrates the importance of having a solution in place that cleanses, verifies and dedupes your data to ensure your customer contacts are valid from the start. Learn why implementing a data cleansing solution is an essential part of doing business, and how it can help you: Improve deliverability Increase customer satisfaction Qualify for postal discounts And more! Download our whitepaper today and find out what bad data is costing you!


Companies increasingly struggle to manage data sufficiently to deliver business value more effectively. This challenge stems from mounting pressures ranging from the rate of change in modern business systems, the ease of creating data silos, and the expanding ways users need and want to work with data. As a result, companies focus on transformative efforts to become more agile, responsive, competitive, and innovative—putting strain and increased pressure on data management programs. Data fabric, an architectural design concept that establishes a consistent set of capabilities and services across the data and analytics ecosystem for data consumers, represents a solution to data management overload. Download this special white paper for in-depth information on data fabric strategy and concepts, architecture, components, and technologies to support the needs of your data consumers.


As today’s data management landscape becomes increasingly complex, it is difficult to offer a unified view of the data to business applications, and to guarantee that governance policies and rules are enforced across the data delivery chain. The logical data fabric is a vision of a unified data delivery platform that solves today’s most complex data management problems. Read this whitepaper to learn: What is a data fabric Different approaches to a data fabric implementation What constitutes a logical data fabric Key benefits of a logical data fabric


Cloud deployments are an ever-moving, ever-changing target, so it’s important to continuously assess and improve data management processes and procedures accordingly. Download this special report to dive into best practices for managing data within today’s cloud environments.


In these complimentary chapters from O’Reilly, you will explore the essential ingredients of designing scalable solutions, including replication, state management, load balancing, and caching. Ultimately, you’ll learn the design principles and key concepts of distributed systems including: Scalability and architecture trade-offs Scaling out the database with caching Distributed the database Consensus in distributed systems Time in distributed systems


In this guide, we’ll discuss what it takes to plan, design, and execute on your data mesh strategy, through the lens of successful implementations at Intuit, Zalando, BlaBlaCar, and others.


As data pipelines grow in size and complexity, DataOps continues to gain a bigger foothold in enterprises hungry for fast, actionable insights. DataOps brings people, processes, and technology together to orchestrate the effective, efficient, and secure flow of data. To do that, organizations must have in place key components in all three areas. Download this special report for a better understanding of the key technologies, strategies, and use cases that are unlocking the power of DataOps at enterprises today.


Data-driven enterprises do not exist on data on their own; they require an advanced, responsive data architecture to gain ground within their markets. Download this special report for best practices of leaders in data-driven architecture who have established high-producing data architectures.


TODAY’S ENTERPRISES are more distributed than ever before—both in terms of employees working across different geographical locations and the dispersal of data across different departments, applications, databases, on-prem data centers, and clouds. This expansion of enterprise data landscapes offers opportunities and challenges for IT leaders and data management professionals. Succeeding in this increasingly distributed, complex world requires rethinking traditional approaches to data architecture and key data management processes around integration, governance, and security. Download this special report for key considerations to achieving real data democratization.


The database world has been changing dramatically over the past decade, and the pace of change has been accelerating in recent years. Ensuring a smooth-running, high-performing database environment today means rethinking how data flows, where it flows, and who oversees the flow. Download this special report to learn about the new technologies and strategies for managing database performance in the modern enterprise.


The future of databases is in the cloud, but achieving higher levels of growth and agility can be hampered by persistent myths. Oracle Corporation, which offers its own proprietary cloud platform, has promoted fear, uncertainty, and doubt about the viability of running Oracle databases on robust, competitive cloud platforms such as Amazon Web Services (AWS). As a result, it is understandable when some IT leaders and database teams hesitate to migrate their Oracle databases. This paper explores and debunks the leading myths that inhibit organizations from migrating, and the realities of how they benefit from moving databases and applications to more flexible and scalable cloud environments.


To examine how database environments and roles are changing within enterprises – as well as how deeply new modes of collaboration and technology are being adopted – Unisphere Research recently conducted a survey of DBTA subscribers in partnership with Quest. From cloud and automation to the rise of "Ops" culture, the world of database management is evolving with new challenges and opportunities emerging for IT leaders and database professionals. Download this special study for a first-hand look at the results and learn where database management is heading.


The challenge for multi-cloud and hybrid environments is to live up to their promise of enabling organizations to be more flexible and agile without the overhead incurred from system complexity. Data management needs to achieve this as well. Developing a well-functioning, hybrid, multi-cloud management strategy requires a number of considerations. Download this report today to dive into key strategies.


As data environments continue to grow in size and complexity, spanning on-premises and cloud sites, effective data integration and governance processes are paramount. Download this special report for the latest trends and strategies for success.


For database managers and users, moving to the cloud means breaking through the confines imposed by capacity ceilings, speed limits, performance issues, and security concerns. At the same time, moving to the cloud does not mean outsourcing control or responsibility for data to an outside provider, and care must be taken to ensure migrations take place with as little disruption to the business as possible. In addition, organizations need to be prepared with the specific skills required to migrate to and manage databases in the cloud. Download this white paper for the questions you need to ask before undertaking a cloud migration.


Deploying today’s flexible technology services and components— containers, microservices, and cloud-based infrastructure—may bring measures of improved agility to IT and data management operations, but translating this into business agility is what makes these technologies impactful. Here’s where an agile technology architecture demonstrates its true value. Download this special report for key capabilities and best practices for success.


Database management today is flush with new challenges and opportunities. More than ever before, businesses today desire speed, scalability, and flexibility from their data infrastructure. At the same time, the complexity of data environments continues to grow – spread across different database types and brands, applications, and on-premise and cloud sites. This makes new technologies and strategies critical. Download this special report today for key practices to managing databases in this highly diverse, emerging landscape.


Meeting the demands of the rapid evolution to real-time business requires new perspectives and approaches. Download this report for seven recommendations to make the most of real-time capabilities today.


Many organizations’ data assets are hidden away in silos or proprietary applications, which can take great amounts of time and resources to locate. This is made more complicated as the amount of data flowing through, into, and out of enterprises keeps growing exponentially. Data catalogs can enable self-service analytics and data lake modernization, as well as support data governance, privacy, and security initiatives. Download this special report, sponsored by Sandhill Consultants, to dive into best practices for harnessing the power of data catalogs in the enterprise today.


Despite greater awareness of threats, protecting data has not become easier in recent years. Data is being created at a rapid clip and there are more ways than ever before to store it. Understanding today’s data security and governance problems is the first step to solving them. Download this special report for 10 key tenets for improving data security and governance in today’s complex data environments.


There is one clear direction data management has been going in as of late – to the cloud. The availability of cloud resources provides new options for building and leveraging enterprise-scale data environments. Support for hybrid and multi-cloud data warehousing is becoming mainstream, edge analytics adoption is rising, and the demand for real-time analytics capabilities is soaring. As more organizations invest in data warehouse and data lake modernization, these areas are also converging with concepts such as the “data lakehouse” and the “data mesh.” Download this special report to navigate the growing constellation of technologies and strategies emerging in modern data management and analytics today.


At a time when enterprises are seeking to leverage greater automation and intelligence, many are becoming acquainted with the advantages of using knowledge graphs to power real-time insights and machine learning. In fact, Gartner predicts that, by 2023, graph technology will play a role in the decision-making process for 30% of organizations worldwide. Download this special report to understand how knowledge graphs are accelerating analytics and AI in the enterprise today.


There’s no turning back from cloud as an enterprise data platform, and adoption continues to expand rapidly. The question is not whether to pursue a cloud strategy, but how to do so to meet your organization’s business requirements most efficiently and cost-effectively. Download this special report to gain a deeper understanding of emerging best practices, key enabling technologies, challenges, and solutions in the evolving world of cloud and data management.


DataOps helps to improve processes throughout the data lifecycle – from initial collection and creation to delivery to the end user, but implementing the methodology requires effort. Download this special report to learn the ten key tenets for a successful DataOps implementation.


Now, more than ever, businesses want scalable, agile data management processes that can enable faster time to market, greater self-service capabilities, and more streamlined internal processes. Download this report for seven key steps to designing and promoting a modern data architecture that meet today’s business requirements.


With all that’s happened in the past 2 years, it is often observed that there may be more risk in staying with the status quo than moving forward and trying something new. Today, agility, enabled by modern methodologies, such as DataOps and DevOps, and the use of new technologies, like AI and machine learning, is critical for addressing new challenges and flexibly pivoting to embrace new opportunities. As we get further into 2022, the annual Data Sourcebook issue puts the current data scene in perspective and looks under the covers of the key trends in data management and analytics. Download your copy today.


In keeping up with the demands of a digital economy, organizations struggle with availability, scalability, and security. For users of the world’s most popular enterprise database, Microsoft SQL Server, this means evolving to deliver information in a hybrid, multi-platform world. While the data platform has long been associated with the Windows Server operating system, many instances can now be found running within Linux environments. The increasing movement toward cloud, which supports greater containerization and virtualization, is opening platform independence in ways not previously seen, and enterprises are benefitting with greater flexibility and lower costs. Download this special white paper today to learn about the era of the amplified SQL Server environment supported by the capabilities of Linux and the cloud.


From the rise of hybrid and multi-cloud architectures to the impact of machine learning, automation, and containerization, database management today is rife with new opportunities and challenges. Download this special report today for the top 9 strategies to overcome performance issues.


In a hybrid, multi-cloud world, data management must evolve from traditional, singular approaches to more adaptable approaches. This applies to the tools and platforms that are being employed to support data management initiatives – particularly the infrastructure-as-a-service, platform-as-a-service, and SaaS offerings that now dominate the data management landscape. Download this special report today for new solutions and strategies to survive and thrive in the evolving hybrid, multi-cloud world.


Data management is changing. It’s no longer about standing up databases and populating data warehouses; it’s about making data the constant fuel of the enterprise, accessible to all who need it. As a result, organizations need to be able to ensure their data is viable and available. Download this special report for the key approaches to developing and supporting modern data governance approaches to align data to today’s business requirements.


Today’s emerging architecture is built to change, not to last. Flexible, swappable systems, designed to be deployed everywhere and anywhere, and quickly dispensed at the end of their tenure, are shifting the dynamics of application and data infrastructures. The combination of containers and microservices is delivering a powerful one-two punch for IT productivity. At the same time, the increasing complexity of these environments brings a new set of challenges, including security and governance, and orchestration and monitoring. Download this special report for guidance on how to successfully leverage the flexibility and scalability that containers and microservices offer while addressing potential challenges such as complexity and cultural roadblocks.


The database is no longer just a database. It has evolved into the vital core of all business activity; the key to market advancement; the essence of superior customer experience. In short, the database has become the business. What role does the new data environment—let’s call it “the era of data races”—play in moving enterprises forward? Download this special report to learn about the ways emerging technologies and best practices can support enterprise initiatives today.


Companies embarking on significant Hadoop migrations have the opportunity to advance their data management capabilities while modernizing their data architectures with cloud platforms and services. Consequently, having a comprehensive approach reduces the risk of business disruption and/or the potential for data loss and corruption. Download this special eGuide today to learn the do’s and don’ts for migrating Hadoop data to the cloud safely, securely, and without surprises, and key architecture strategies to follow.


To successfully make the journey to a data-driven enterprise, businesses are under pressure to extract more value from their data in order to be more competitive, own more market share and drive growth. This means they have to make their data work harder by getting insights faster while improving data integrity and resiliency, leverage automaton to short cycle times and reduce human error, and adhere to data privacy regulations. DataOps opens the path to delivering data through the enterprise as its needed, while maintaining its quality and viability. In this thought leadership paper, we will provide perspectives on the advantages DataOps gives to stakeholders across the enterprise, including database administrators, data analysts, data scientists, and c-level executives.


With more data than ever flowing into organizations and stored in multiple cloud and hybrid scenarios, there is greater awareness of the need to take a proactive approach to data security. Download this special report for the top considerations for improving data security and governance from IT and security leaders today.


There are many types of disruption affecting the data management space, but nowhere will the impact be more substantial than at the edge. Leading operations moving to the edge include smart sensors, document and data management, cloud data processing, system backup and recovery, and data warehouses. Download this special report for the key transformational efforts IT leaders need to focus on to unlock the power of IoT and the edge.


For organizations with growing data warehouses and lakes, the cloud offers almost unlimited capacity and processing power. However, transitioning existing data environments from on-premises systems to cloud platforms can be challenging. Download this special report for key considerations, evolving success factors and new solutions for enabling a modern analytics ecosystem.


Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language models are able to represent the relationships and accurate meaning of data instead of simply generating words based on patterns. Download this special report to dive into key uses cases, best practices for getting started, and technology solutions every organization should know about.


From the rise of hybrid and multi-cloud architectures, to the impact of machine learning and automation, the business of data management is constantly evolving with new technologies, strategies, challenges, and opportunities. The demand for fast, wide-ranging access to information is growing. At the same time, the need to effectively integrate, govern, protect, and analyze data is also intensifying. Download this special report for the top trends in data management to keep on your radar for 2021.


DataOps is now considered to be one of the best ways to work toward a data-driven culture and is gaining ground at enterprises hungry for fast, dependable insights. Download this special report to learn about the key technologies and practices of a successful DataOps strategy.


The move to modern data architecture is fueled by a number of converging trends – the rise of advanced data analytics and AI, the Internet of Things, edge computing, and cloud. Both IT and business managers need to constantly ask whether their data environments are robust enough to support the increasing digitization of their organizations. Over the past year, requirements for data environments have been driven largely by cost considerations, efficiency requirements, and movement to the cloud. Download this special report for emerging best practices and key considerations today.


Now, more than ever, the ability to pivot and adapt is a key characteristic of modern companies striving to position themselves strongly for the future. Download this year’s Data Sourcebook to dive into the key issues impact enterprise data management today and gain insights from leaders in cloud, data architecture, machine learning, data science and analytics.


This study, sponsored by Quest Software, includes the views and experiences of 285 IT decision makers, representing a fairly broad sample of company types and sizes. The survey found that databases continue to expand in size and complexity, while at the same time, more enterprises are turning to cloud-based resources to keep information highly available.


The critical role of data as fuel for the growing digital economy is elevating data managers, DBAs, and data analysts into key roles within their organizations. In addition, this rapid change calls for a three-pronged approach that consists of expanding the use of more flexible cloud computing strategies, growing the automation of data environments, and increasing the flow of data and collaboration through strategies such as DevOps and DataOps. Download this special report today to better understand the emerging best practices and technologies driving speed and scalability in modern database management.


A strong data management foundation is essential for effectively scaling AI and machine learning programs to evolve into a core competence of the business. Download this special report for the key steps to success.


Today’s enterprises rely on an assortment of platforms and environments, from on-premise systems to clouds, hybrid clouds and multi-clouds. This calls for modern data management practices that leverage emerging technologies, providing enterprise decision managers with the tools and insights they need to improve and transform their businesses. Download this special report for best practices in moving to modern data management standards to ensure the integration and governance of valuable data sources within today’s diverse environments.


Emerging agile technologies and techniques are leading to new ways of accessing and employing data. At the same time, the increasing complexity of these environments is creating additional challenges around security and governance, and orchestration and monitoring, which is particularly evident with the rise of hybrid, multi-cloud enterprise environments. Welcome to the era of the digitally enriched platform. Download this special report today to dive into emerging technologies and best practices.


AIOps market is set to be worth $11B by 2023 according to MarketsandMarkets. Originally started as automating the IT operations tasks, now AIOps has moved beyond the rudimentary RPA, event consolidation, noise reduction use cases into mainstream use cases such as root causes analysis, service ticket analytics, anomaly detection, demand forecasting, and capacity planning. Join this session with Andy Thurai, Chief Strategist at the Field CTO ( thefieldcto.com) to learn more about how AIOps solutions can help the digital business to run smoothly.


A challenge of ML is operationalizing the data volume, performance, and maintenance. In this session, Rashmi Gupta explains how to use tools for orchestration and version control to streamline datasets. She also discusses how to secure data to ensure that production control access is streamlined for testing.


As market conditions rapidly evolve, DataOps can help companies produce robust and accurate analytics to power the strategic decision-making needed to sustain a competitive advantage. Chris Bergh shares why, now more than ever, data teams need to focus on operations, not the next feature. He also provides practical tips on how to get your DataOps program up and running quickly today.


Traditional methodologies for handling data projects are too slow to handle the teams working with the technology. The DataOps Manifesto was created as a response, borrowing from the Agile Manifesto. This talk covers the principles of the DataOps Manifesto, the challenges that led to it, and how and where it's already being applied.


The ability to quickly act on information to solve problems or create value has long been the goal of many businesses. However, it was not until recently that new technologies emerged to address the speed and scalability requirements of real-time analytics, both technically and cost-effectively. Attend this session to learn about the latest technologies and real-world strategies for success.


Each week, 275 million people shop at Walmart, generating interaction and transaction data. Learn how the company's customer backbone team enables extraction, transformation, and storage of customer data to be served to other teams. At 5 billion events per day, the Kafka Streams cluster processes events from various channels and maintains a uniform identity of each customer.


To support ubiquitous AI, a Knowledge Graph system will have to fuse and integrate data, not just in representation, but in context (ontologies, metadata, domain knowledge, terminology systems), and time (temporal relationships between components of data). Building from ‘Entities’ (e.g. Customers, Patients, Bill of Materials) requires a new data model approach that unifies typical enterprise data with knowledge bases such as industry terms and other domain knowledge.


We are at the juncture of a major shift in how we represent and manage data in the enterprise. Conventional data management capabilities are ill equipped to handle the increasingly challenging data demands of the future. This is especially true when data elements are dispersed across multiple lines of business organizations or sourced from external sites containing unstructured content. Knowledge Graph Technology has emerged as a viable production ready capability to elevate the state of the art of data management. Knowledge Graph can remediate these challenges and open up new realms of opportunities not possible before with legacy technologies.


Knowledge Graphs are quickly being adopted because they have the advantages of linking and analyzing vast amounts of interconnected data. The promise of graph technology has been there for a decade. However, the scale, performance, and analytics capabilities of AnzoGraph DB, a graph database, is a key catalyst in Knowledge Graph adoption.


Though MongoDB is capable of incredible performance, it requires mastery of design to achieve such optimization. This presentation covers the practical approaches to optimization and configuration for the best performance. Padmesh Kankipati presents a brief overview of the new features in MongoDB, such as ACID transaction compliance, and then move on to application design best practices for indexing, aggregation, schema design, data distribution, data balancing, and query and RAID optimization. Other areas of focus include tips to implement fault-tolerant applications while managing data growth, practical recommendations for architectural considerations to achieve high performance on large volumes of data, and the best deployment configurations for MongoDB clusters on cloud platforms.


Just as in real estate, hybrid cloud performance is all about location. Data needs to be accessible from both on-premise and cloud-based applications. Since cloud vendors charge for data movement, customers need to understand and control that movement. Also, there may be performance or security implications around moving data to or from the cloud. This presentation covers these and other reasons that make it critical to consider the location of your data when using a hybrid cloud approach.


What if your business could take advantage of the most advanced AI platform without the huge upfront time and investment inherent in building an internal data scientist team? Google’s Ning looks at end-to-end solutions from ingest, process, store, analytics, and prediction with innovative cloud services. Knowing the options and criteria can really accelerate the organization's AI journey in a quicker time frame and without significant investment.


After 140+ years of acquiring, processing and managing data across multiple business units and multiple technology platforms, Prudential wanted to establish an enterprise wide data fabric architecture to allow data to be available where and when its needed. Prudential chose data virtualization technology to create the logical data fabric that spans their entire enterprise.


The pace of technology change is continuing to accelerate and organizations have no shortage of tool and application options. But while many are modernizing tool infrastructure and ripping out legacy systems, the data that powers new tools still presents difficult and seemingly intractable problems. Seth Earley discusses approaches for bridging the gap between a modernized application infrastructure and ensuring that quality data is available for that infrastructure.


As business models become more software driven, the challenge of maintaining reliable digital services and delightful customer experiences, as well as keeping those services and customer data safe is a "continuous" practice. It’s particularly important now, when the COVID-19 global pandemic has created a discontinuity in digital transformation and many industries have been forced entirely into a digital business model due to social distancing requirements. Bruno Kurtic discusses the impact of the pandemic on industries and digital enterprises leverage continuous intelligence to transform how they build, run, and secure their digital services and use continuous intelligence to outmaneuver their competition.


In this session, Lee Rainie discusses public attitudes about data, machine learning, privacy, and the role of technology companies in society—including in the midst of COVID-19 outbreak. He covers how these issues will be factors shaping the next stages of the analytics revolution as politicians, regulators, and civic actors start to focus their sights on data and its use.


From the rise of hybrid and multi-cloud architectures, to the impact of machine learning and automation, database professionals today are flush with new challenges and opportunities. Now, more than ever, enterprises need speed, scalability and flexibility to compete in today’s business landscape. At the same time, database environments continue to increase in size and complexity; crossing over relational and non-relational, transactional and analytical, and on-premises and cloud sites. Download this report to dive into key enabling technologies and evolving best practices today.


With constantly evolving threats and an ever-increasing array of data privacy laws, understanding where your data is across the enterprise and properly safeguarding it is more important today than ever before. Download this year’s Cybersecurity Sourcebook to learn about the pit­falls to avoid and the key approaches and best practices to embrace when addressing data security, governance, and regulatory compliance.


Today’s organizations want advanced data analytics, AI, and machine learning capabilities that extend well beyond the power of existing infrastructures, so it’s no surprise that data warehouse modernization has become a top priority at many companies. Download this special report to under how to prepare for the future of data warehousing, from increasing impact of cloud and virtualization, to the rise of multi-tier data architectures and streaming data.


As organizations are more likely than ever to be audited by their software vendor, one of the top questions we are asked is, “How at risk is my organization in the event of an Oracle audit?” In this eBook, you will be able to quantify your organization’s Oracle audit risk through traditional risk calculating practices in a risk matrix.


Rapid data collection is creating a tsunami of information inside organizations, leaving data managers searching for the right tools to uncover insights. Knowledge graphs have emerged as a solution that can connect relevant data for specific business purposes. Download this special report to learn how knowledge graphs can act as the foundation of machine learning and AI analytics.


It’s no surprise then that adoption of data lakes continues to rise as data managers seek to develop ways to rapidly capture and store data from a multitude of sources in various formats. However, as the interest in data lakes continues to grow, so will the management challenges. Download this special report for guidelines to building data lakes that deliver the most value to enterprises.


While cloud is seen as the go-to environment for modernizing IT strategies and managing ever-increasing volumes of data, it also presents a bewildering array of options. Download this special report for the nine points to consider in preparing for the hybrid and multi-cloud world.


DataOps is poised to revolutionize data analytics with its eye on the entire data lifecycle, from data preparation to reporting. Download this special report to understand the key principles of a DataOps strategy, important technology, process and people considerations, and how DataOps is helping organizations improve the continuous movement of data across the enterprise to better leverage it for business outcomes.


This book will discuss the ins and outs of Oracle’s licensing web, clarifying the murky points. We’ll also go in-depth on the petrifying and dreaded “Oracle Audit,” providing clear advice on how to prepare for it; advice that includes calling in the cavalry when needed, to protect you from Oracle’s clutches.


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