Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• Cloud database comparison: AWS, Microsoft, Google and Oracle

  Here's a look at the rival cloud database offerings from AWS, Google, Microsoft and Oracle based on their product breadth, migration capabilities and pricing models. Continue Reading

• Evaluating the different types of DBMS products

  The various types of database software come with advantages, limitations and optimal uses that prospective buyers should be aware of before choosing a DBMS. Continue Reading

• On-premises vs. cloud data warehouses: Pros and cons

  Data warehouses increasingly are being deployed in the cloud. But both on-premises and cloud data warehouses have pluses and minuses to consider, as explained here. Continue Reading

• 15 top data governance tools to know about in 2022

  Data governance software can help organizations manage governance programs. Here's a look at the key features and capabilities of 15 prominent governance tools. Continue Reading

• 16 top data catalog software tools to consider using in 2022

  Numerous tools can be used to build and manage data catalogs. Here's a look at the key features, capabilities and components of 16 prominent data catalog tools. Continue Reading

• Best practices and pitfalls of the data pipeline process

  Developing an effective data pipeline process is a key step for organizations to manage data sources, flow and quality. A data pipeline also ensures approved data access.Continue Reading

• New approaches create opportunity to turn data into value

  Bill Schmarzo, a data science industry thought leader, discusses how organizations can reframe their view of data using economic concepts to turn data into value.Continue Reading

• Improve data value by relying on economic principles

  Bill Schmarzo, author of 'The Economics of Data, Analytics, and Digital Transformation,' discusses how organizations can improve data value by incorporating economic concepts.Continue Reading

• The ultimate guide to big data for businesses

  Big data is the fuel for today's analytics applications. This in-depth big data guide explains how businesses can benefit from it and what they need to do to use it effectively.Continue Reading

• Hadoop vs. Spark: An in-depth big data framework comparison

  Hadoop and Spark are widely used big data frameworks. Here's a look at their features and capabilities and the key differences between the two technologies.Continue Reading

• Open source vs. proprietary database management

  Open source and cloud data management are becoming popular options to streamline information data management processes. Also, examine the benefits of on-site, proprietary strategies.Continue Reading

• 5 challenges IT faces using open source data management

  There are a variety of open source challenges for data management software, including lack of real-time BI access, miscalculating costs and underestimating the resources required.Continue Reading

• The benefits and pitfalls of cloud-based data management systems

  Learn the benefits of cloud-based data management systems, common pitfalls and strategies when considering varying data levels and industry needs.Continue Reading

• Bill Inmon's data warehouse approach tackles text analysis

  Learn the fine points of a concept at the heart of 'The Textual Warehouse' a new book that aims to help organizations profit through textual analysis.Continue Reading

• Best practices for cloud database management systems

  Learn best practices to streamline cloud database management to benefit business performance, compliance audits and business continuity.Continue Reading

• What is data architecture? A data management blueprint

  Data architecture is a discipline that documents an organization's data assets, maps how data flows through its systems and provides a blueprint for managing data.Continue Reading

• The pros and cons of big data outsourcing

  More companies are seeking outside help to capitalize on data's value. Examine the benefits and drawbacks that come with outsourcing big data processing projects.Continue Reading

• Data architecture vs. information architecture: How they differ

  Data architects collect the statistics and information architects put the numbers into context as they work symbiotically to bolster an enterprise's data and business strategies.Continue Reading

• The value of PDF data extraction: Sifting for hidden data

  During the process of data cleaning, there's a way to extract valuable hidden data. Learn how in this excerpt from 'Cleaning Data for Effective Data Science.'Continue Reading

• Data modeling vs. data architecture: What's the difference?

  Data modelers and data architects have distinctly different roles, but they work in a complementary fashion to help enterprises unlock and capitalize on data's business value.Continue Reading

• What an automated data integration implementation means

  Automated data integration can reduce time spent by data professionals on repetitive tasks. Learn about strategies to help implement automated data integration.Continue Reading

• Data governance and your master data management strategy

  Strong data governance and master data management strategies typically go hand in hand. Read on to see how key factors of data governance can support your master data management.Continue Reading

• How data governance and data quality work together

  High-quality, reliable data is essential to the data governance process. Here are strategies to ensure data quality standards are ingrained in governance processes.Continue Reading

• How to build an all-purpose big data pipeline architecture

  Like a superhighway system and its many on- and off-ramps, an enterprise's big data pipeline transports infinite amounts of collected data from its sources to its destinations.Continue Reading

• Data quality for big data: Why it's a must and how to improve it

  As data volumes increase exponentially, methods to improve and ensure big data quality are critical in making accurate, effective and trusted business decisions.Continue Reading

• Enterprise augmented data management benefits and growth

  Gartner predicts plenty of growth in the booming augmented data management market, which helps data professionals focus on insights over administrative tasks.Continue Reading

• Why consider an augmented data catalog?

  Automated and augmented data catalogs have been around for a few years, but adoption is still lagging. Find out why an enterprise may consider investing in the technology.Continue Reading

• Why consider an open source data catalog

  Enterprise data catalogs offer organizations plenty of benefits with metadata management and data organization. Find out why some enterprises choose open source data catalogs.Continue Reading

• Top open source database advantages for enterprises

  Open source databases typically offer lower upfront costs and more community support and, in recent years, have offered strong competition to commercial database offerings.Continue Reading

• Bias in big data: How to find it and mitigate influence

  It's no secret that bias exists in large data sets, ; the key is addressing it. With transparency, diversity and accountability, limiting that bias can be possible.Continue Reading

• The differences between a data warehouse vs. data mart

  Data marts and data warehouses are both important in the decision-making process. Here are the biggest differences between the two repositories and why they each matter.Continue Reading

• The top 5 graph database advantages for enterprises

  Graph databases offer plenty of advantages to organizations in the way they connect data points to each other. Read on to see what experts say the top advantages are.Continue Reading

• Data catalog comparison to help you choose your best fit

  Data catalog options vary across vendors, but, as with most decisions in the data realm, it takes self-knowledge to make the right choice and understand each option's capabilities.Continue Reading

• Data fabrics help data lakes seek the truth

  Data fabrics can play a key role in aligning business goals with the integration, governance, reliability and democratization of information collected in massive data lakes.Continue Reading

• Augmented data preparation the next step for self-service BI

  Augmented data tools play a key role in expanding data use across organizations. Read on to find out how augmented data preparation tools democratize data in self-service BI.Continue Reading

• Open source database comparison to choose the right tool

  These are four of the most popular open source relational databases available to enterprises with a comparison chart to help you find the best option to fit your data.Continue Reading

• What FAIR data management means for your enterprise

  The FAIR principles were made to promote the sharing of data in the research field, but their guidance can help organizations in other industries improve their own data practices.Continue Reading

• New data warehouse schema design benefits business users

  The Unified Star Schema is a revolution in data warehouse schema design. Learn the benefits of this new architecture and read an excerpt from a new book about it.Continue Reading

• Data warehouse vs. data lake: Key differences

  Data warehouses and data lakes are both data repositories common in the enterprise, but what are the main differences between the two and which is best for your data?Continue Reading

• Apache Pulsar vs. Kafka and other data processing technologies

  David Kjerrumgaard looks at how the distributed messaging platform Apache Pulsar handles storage compared to Apache Kafka and other data processing technologies.Continue Reading

• The top 6 use cases for a data fabric architecture

  Enterprise data fabric adoption has been on the rise as a way to ensure access and data sharing in a distributed environment. Here are the top use cases for data fabrics.Continue Reading

• Data protection officer responsibilities and role importance

  The data protection officer title has been growing over the last few years, and organizations are still working to grasp the full responsibilities of the role.Continue Reading

• Healthcare data management challenges hold back adoption

  The healthcare industry has had difficulty adopting data management best practices, but a few organizations have tackled the challenges successfully.Continue Reading

• How AI data privacy can help your enterprise

  Enterprises benefit in many ways from AI data privacy tools that reduce the need for manual efforts from data professionals. Read on for top use cases for the growing technology.Continue Reading

• NewSQL databases: The bridge between SQL and NoSQL

  NewSQL databases attempt to provide enterprises with the top benefits of both relational and NoSQL databases on one platform. Here's a look at how NewSQL can benefit enterprises.Continue Reading

• Synthetic data in healthcare advances patient analytics

  Learn how synthetic data in healthcare can be beneficial across the board. Plus, get a sneak peek at a new book on synthetic data generation from O'Reilly Media.Continue Reading

• 3 growing applications of AI in data management

  There are plenty of ways AI can augment data professionals throughout the data pipeline, from sifting through large data sets for duplicates to easing the preparation process.Continue Reading

• Why you should consider a machine learning data catalog

  A machine learning data catalog can benefit an enterprise in a variety of ways, from increasing access to necessary data to keeping your data sources up to date.Continue Reading

• How to streamline your data cleansing process

  Data cleansing is an important part of maintaining data quality, and the process is easier if you keep ahead of it by upholding governance and quality standards.Continue Reading

• Top 7 data catalog use cases for enterprises

  From data lake modernization to data democratization, there are many benefits to a data catalog. Experts talk about the top ways data catalog adoption can benefit enterprises.Continue Reading

• Metamorphosis of Kafka Confluent event streaming technologies

  Kafka Confluent event streaming tools allow data managers, analysts and developers to capture, process, store, access and analyze data streams on the fly with precision.Continue Reading

• Key to data management in oil and gas is stability

  Ensuring quality data management and analytics comes from following best practices, proper commitment from your organization and sticking with the plan.Continue Reading

• How to choose the right database to fit your data model(s)

  Choosing the right database for your enterprise applications can be a difficult process. Read on for some considerations on data platforms and model needs before making the choice.Continue Reading

• Key factors for successful data lake implementation

  There are many important parts to a data lake implementation, from technology to governance. Read on for the top factors to evaluate in your implementation strategy.Continue Reading

• 10 chief data officer trends that are reshaping the role

  The chief data officer role is appearing in more industries and changing in responsibilities. Experts talk about the ways the position is evolving across enterprises.Continue Reading

• Trusted data is among governance, data integration benefits

  Well-conceived governance programs injected with data integration tools can overcome the inherent distrust companies have in their own data stored in multiple systems.Continue Reading

• Choosing a modern data warehouse to fit your data needs

  Choosing the right modern data warehouse for your enterprise data is a large task. Here are the key evaluation points to consider when choosing your platform.Continue Reading

• Benefits of a data catalog and why you need one

  Data catalogs help across enterprises, from breaking down data silos to ensuring data privacy. A new book from Technics Publications explains the benefits of data catalogs.Continue Reading

• Alternative data in finance holds potentials and risks

  Alternative data sources, when verified as reliable and trustworthy, can be an essential tool for financial institutions when it comes to gathering information.Continue Reading

• Top -- and bottom -- 5 Apache Kafka use cases

  Apache Kafka has many applications in big data, but what enterprise use cases are the best fit for the tool? Experts discuss where Kafka works best for your data.Continue Reading

• Master data management best practices for insurers

  For insurers, master data management holds the potential to make how they operate more efficient and effective but requires company commitment and investment.Continue Reading

• How data governance and data management work together

  Data governance is an important part of data management. These recommendations will help build a strong complementary relationship between the two strategies.Continue Reading

• Pros and cons of the 4 best IPaaS software options

  Integrating with your cloud data? Choosing between IPaaS software and vendors can be difficult. Here is a breakdown of four of the top-choice vendor offerings on the market.Continue Reading

• The rise of multimodel databases to support data variety

  Polyglot persistence has been the predominant answer to supporting diverse data models. But to optimize a variety of data, multimodel databases have been gaining popularity.Continue Reading

• Data hub vs. data lake: Deciphering the differences

  Data lakes and data hubs are approaches to data management that are typically opposed. Here are the main differences between these two storage options.Continue Reading

• 3 of the top use cases for graph databases

  Graph databases establish many unique relationships between data points. These unusual relationships are beneficial in many use cases, but here are the top three.Continue Reading

• Data governance metrics: Data quality, data literacy and more

  Statistics on data quality are the most common metrics used to track data governance programs, but other types of data-related measurements also can be applied.Continue Reading

• NoSQL database comparison to help you choose the right store

  With so many NoSQL databases to choose from, how can you tell which is best for your data set? Check out this comparison of some of the most popular NoSQL databases.Continue Reading

• What are the main features of data catalog software?

  Data catalogs are curated data portals for self-service analytics users. Learn about the capabilities of data catalog tools, vendors that sell them and how catalogs work.Continue Reading

• Evaluate your data governance and privacy best practices

  GDPR and CCPA have put data governance in the news. With this increase in data legislation, now is a great time to review your company's data governance policies.Continue Reading

• Evaluating data warehouse platform options and your need for one

  There's still a place for data warehouses in data architectures. But first, ask whether your organization needs one and what type of technology platform is the best fit.Continue Reading

• Apache Kafka version 2.4 improves streaming data performance

  The latest release of the Apache Kafka open source event streaming platform adds improved replication and availability capabilities to help boost overall performance.Continue Reading

• Data warehouse technologies evolve as vendors look skyward

  The need for high-speed analytics and low latency are pushing data warehousing vendors to create and reinvent their platforms and, in some cases, reinvent themselves.Continue Reading

• Future of MongoDB could be brighter than other NoSQL engines

  Top NoSQL database MongoDB, once thought of as a revolution in data management, has come back to Earth some, but it still has a chance to stay ahead of competitors.Continue Reading

• How AI could save the enterprise data catalog

  Enterprise data catalogs record all the databases and files in a corporation, but sometimes it can become out of date. Advances in AI are helping minimize the problem.Continue Reading

• Data integration vs. ETL in the age of big data

  Data integration provides a consistent view of business performance across multiple data sources, though it needs to keep up with the changing needs of organizations and the big data revolution.Continue Reading

• Immuta introduces new features to Automated Data Governance

  The new updates also bring about native Hadoop distributed file system workspaces within Immuta and more ways to integrate Immuta with other applications and tools.Continue Reading

• Third-party database tools boast attractive alternatives

  For companies considering third-party database tools, this handbook provides expert advice on evaluating and deploying on-premises and cloud options from third parties.Continue Reading

• Database management tools from third parties make natives restless

  Third-party database performance tools offer attractive alternatives to management software from DBMS vendors, provided their capabilities include orchestration, governance and integration.Continue Reading

• Weighing the use of third-party database administration tools

  Database expert Chris Foot details the key reasons why DBAs should consider using third-party database administration to fill gaps left by the major database manufacturers.Continue Reading

• 10 Apache Kafka best practices for data management pros

  How can data management teams most effectively deploy and use Apache Kafka in data pipelines and streaming applications? Here are some key guidelines to follow.Continue Reading

• Data management roles: Data architect vs. data engineer, others

  Veteran data pro Michael Bowers differentiates between key data management positions, including their salaries and which ones can add the most business value.Continue Reading

• SQL Server in Azure database choices and what they offer users

  SQL Server databases can be moved to the Azure cloud in several different ways. Here's what you'll get from each of the options for migrating SQL Server to Azure.Continue Reading

• Key components of an effective data virtualization architecture

  Experts break down which elements -- both technical and nontechnical -- are most crucial to successfully deploying and managing a data virtualization architecture.Continue Reading

• Big data containers gain wider appeal in system deployments

  This handbook examines the use of Docker containers in Kubernetes clusters to run big data systems and offers insight on container deployment and management issues.Continue Reading

• Container technologies promise more agility for big data apps

  Along with the ability to provide greater agility and flexibility for big data applications, containers can play a role in IT strategy that drives real-time decision-making.Continue Reading

• Explore data integration products for your organization

  Browse through the current data integration products currently available to help you determine which tool best suits your organization's needs.Continue Reading

• A comparison of open source, real-time data streaming platforms

  With so many real-time data streaming tools, how do you know which is right for your organization? Experts compare Spark Streaming, Kafka Streams, Flink and others.Continue Reading

• Data virtualization tools promote anywhere, anytime data access

  This online handbook examines data virtualization software and how organizations are deploying and using the technology as part of their data integration processes.Continue Reading

• Data virtualization benefits seen in unified views, IT agility

  Through in-place integration, data virtualization platforms can provide wider access to data and simplify security and governance. But they come with some limitations.Continue Reading

• Data virtualization use cases cover more integration tasks

  In a Q&A, Gartner analyst Mark Beyer discusses user adoption of data virtualization software and the wider data integration uses that the technology is now handling.Continue Reading

• Microservices and big data start to get closer

  Microservices are riding a wave of user interest, leading to changes in IT operations. ThoughtWorks expert Zhamak Dehghani discusses what that means for big data.Continue Reading

• The evolution of the data preparation process and market

  Organizations have long struggled with inconsistent data and other issues. Expert Andy Hayler explores how that has led to the rise of the data preparation tools market.Continue Reading

• GDPR privacy concerns still brewing on law's first birthday

  The first year of the much-debated EU data protection rule was subdued. High-profile fines for privacy breaches have yet to come, but regulators are starting to take action.Continue Reading

• The main picks for Hadoop distributions on the market

  Check out the current top Hadoop distribution vendors in the market to help you determine which product is best for your company.Continue Reading

• Inside view of Tibco integration architecture planning

  Tibco's acquisitions of well-regarded, small software specialists such as SnappyData are part of a drive toward what it calls 'connected intelligence.' CTO Nelson Petracek provides background.Continue Reading

• Advice on enterprise data cleansing from an SAP VP

  SAP's Kristin McMahon details data cleansing best practices and explains why a good data cleanse needs continual communication, collaboration and oversight.Continue Reading

• Data modeling software tackles glut of new data sources

  Data modeling platforms are starting to incorporate features to automate data-handling processes, but IT must still address entity resolution, data normalization and governance.Continue Reading

• Find the best data integration tools for your organization

  Read analysis and comparisons of data integration tools to help you select the right platform from the leading commercial and open source products currently on the market.Continue Reading

• 4 factors to consider in a Hadoop distributions comparison

  Examine the key characteristics necessary to evaluate in a Hadoop distribution comparison, focusing on enterprise features, subscription options and deployment models.Continue Reading