Evaluate
Weigh the pros and cons of technologies, products and projects you are considering.
Evaluate
Weigh the pros and cons of technologies, products and projects you are considering.
Different types of database management systems explained
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
Trusted data is the foundation of data-driven decisions, GenAI
Any organization that wants to drive decision-making with data or use generative AI won't succeed without understanding how to cultivate trusted data. 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
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Data management and governance key to successful AI use
AI's effectiveness is limited by data quality. Building strong data management and governance programs are crucial to handling the challenges that AI presents to organizations. Continue Reading
Real-time analytics, vector search accelerate time to insights
Real-time analytics and vector search capabilities reduce time to insights, enabling data-driven organizations to make faster decisions and generate value from their data. Continue Reading
18 top data catalog software tools to consider using in 2024
Numerous tools can be used to build and manage data catalogs. Here's a look at the key features, capabilities and components of 18 prominent data catalog tools.Continue Reading
18 top big data tools and technologies to know about in 2024
Numerous tools are available to use in big data applications. Here's a look at 18 popular open source technologies, plus additional information on NoSQL databases.Continue Reading
16 top data governance tools to know about in 2024
Data governance software can help organizations manage governance programs. Here's a look at the key features and capabilities of 16 prominent governance tools.Continue Reading
Unlock the value of data through AI, modern data platforms
Organizations looking to harness the power of generative AI to unlock data value should combine it with the modern data platform to maximize performance and efficiency.Continue Reading
Companies still grappling with building modern data platforms
Data platforms are crucial for managing and delivering data efficiently, but a recent survey from Enterprise Strategy Group showed that companies still struggle to implement them.Continue Reading
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Why non-invasive data governance is the best approach to use
Organizations typically approach data governance with top-down or traditional approaches. Consultant Robert Seiner discusses what makes his non-invasive approach the best option.Continue Reading
Explore the benefits of AI for DataOps
Enterprise Strategy Group research shows most organizations feel they need AI to unlock the full potential of DataOps and improve data pipeline performance.Continue Reading
Organizations identify DataOps as driver to improve data use
An overwhelming majority of organizations report plans to increase DataOps spending. Continued investments target real-time, quality data-driven decision-making and insights.Continue Reading
GenAI, Vector AI Search, multi-cloud top Oracle CloudWorld
Oracle CEO paints a bright picture of the future with generative AI, shares integration plans and expands Microsoft partnership.Continue Reading
Security a top challenge in building a modern data platform
Modern data platforms help manage large volumes of data and empower real-time decision-making. It starts with overcoming the top challenges organizations identify.Continue Reading
Data quality fuels analytics, AI
Data quality is tied to organizations' ability to gain actionable data from analytics and AI processes, and orgs that implement data quality tools can make faster decisions.Continue Reading
Cloud data warehouse book challenges data assumptions
Dr. Barry Devlin's book lays out the principles of cloud data warehousing and challenges data managers to evaluate what they need when choosing a data warehouse approach.Continue Reading
Evaluate cloud data warehouses based on data, outcomes
Organizations must focus on data and desired outcomes -- and question their assumptions -- when evaluating cloud data warehouse needs, according to industry expert Dr. Barry Devlin.Continue Reading
6 ways Amazon Security Lake could boost security analytics
Amazon's new security-focused data lake holds promise -- including possibly changing the economics around secure data storage.Continue Reading
Data stack benefits evolve with modernization
Modernizing data operations changes the way organizations use data stacks. Industry experts share definitions for the new form of data stacks, what it includes and its benefits.Continue Reading
Empower decision-making with real-time insights
Using the right strategies is a crucial key to unlocking the benefits of real-time analytics and empowering organizations with agile data-driven decision-making.Continue Reading
Mainframe databases teach an old dog new survival tricks
Long predicted to fade away in favor of more modern architectures, mainframes still play an integral role in corporate IT strategies, thanks to advances in database software.Continue Reading
Data mesh vs. other data management options
Data mesh takes a decentralized approach to data management and deriving value from data. It shares similarities with data warehouses, lakes and fabrics, but differs in philosophy.Continue Reading
Informatica World 2023: Cloud, data and AI together
Informatica launched the generative AI Claire GPT product and plans to offer Intelligent Data Management Cloud as a Microsoft Azure Native ISV Service.Continue Reading
Modernizing a data warehouse for real-time decisions
Updating a data warehouse to improve scalability, flexibility, security and speed is necessary to keep pace with real-time analytics demands.Continue Reading
Benefits of data mesh might not be worth the cost
Data mesh can improve an organization's data quality and insights, but significant challenges can make these benefits difficult to achieve.Continue Reading
Book excerpt: Data mesh increases data access and value
Zhamak Dehghani, a pioneer in data mesh technology, discusses how the concept decentralizes data to improve data-related decision-making and value in her book.Continue Reading
What's all this talk about data mesh?
Data mesh brings a variety of benefits to data management, but it also presents challenges if organizations don't have the right culture and infrastructure in place.Continue Reading
ESG predicts 2023 shifts for DataOps, data management
Organizations are using cloud technologies and DataOps to access real-time data insights and decision-making in 2023, according to Enterprise Strategy Group research.Continue Reading
Data lake vs. data warehouse: Key differences explained
Data lakes and data warehouses are both commonly used in enterprises. Here are the main differences between them to help you decide which is best for your data needs.Continue Reading
Data-centric developer responsibilities evolve in 2022
Enterprise Strategy Group Analyst Stephen Catanzano discusses how data-centric developer responsibilities are evolving as technological advancements enable more data use.Continue Reading
Organizations capitalize on intelligent data management
Intelligent data management concepts are opening new avenues for organizations to make better data-centric decisions and extract more value from their data.Continue Reading
5 pillars of data observability bolster data pipeline
Data observability provides holistic oversight of the entire data pipeline in an organization. Use the five pillars to ensure efficient, accurate data operations.Continue Reading
Comparing DBMS vs. RDBMS: Key differences
A relational database management system is the most popular type of DBMS for business uses. Find out how RDBMS software differs from other DBMS technologies.Continue Reading
The differences between a data warehouse vs. data mart
Data marts and data warehouses both play key roles in the BI and analytics process. Here's how they differ and how they can be used to help drive business decisions.Continue Reading
AWS DataZone headlines AWS re:Invent 2022
AWS DataZone will enable the sharing, search and discovery of data at scale with less risk. It is one of many data advancements announced at AWS re:Invent 2022.Continue Reading
Evaluating data warehouse deployment options and use cases
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
7 expert recommended data observability tools
Commercial data observability tools can offer organizations pre-built components and plenty of vendor support for data use cases including monitoring, security and decision-making.Continue Reading
6 data observability open source tools to consider
Learn about six data observability open source options helping organizations pursue data science experiments that are more budget-friendly and flexible than commercial tools.Continue Reading
Big Data London focuses on future of data-driven strategies
At Big Data London, data quality and intelligence took center stage as companies strive for fast and efficient delivery of quality information -- and the vendors to make it happen.Continue Reading
The future of DataOps trends in 2023 and beyond
DataOps is a growing tool for organizations looking to efficiently distribute accurate data to users. Learn the DataOps trends teams must understand as it evolves.Continue Reading
7 top data quality management tools
Data quality management tools help organizations automate and fill gaps in data processes from lacking quality to dated analytics. Here are seven of the top tools in the market.Continue Reading
7 data quality best practices to improve data performance
Data quality is essential to operate a successful data pipeline and enable data-driven decision-making. These seven data quality best practices can help improve performance.Continue Reading
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
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 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
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
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