Features

Features

• American Airlines lowers data management costs with Intel

  As the airline giant moves more of its data workloads to the cloud, tools from Intel's Granulate are making platforms such as Microsoft's Azure Data Lake more efficient.  Continue Reading

• Do traditional data stacks have a use versus modern options?

  Traditional data stacks differ from modern data stacks in the use of cloud and advanced analytics tools. Update on-premises data stacks to gain niche advantages over cloud options.  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

• Use knowledge graphs with databases to uncover new insights

  Knowledge graphs work with graph databases to offer different data storage options than a traditional database, particularly in the biomedical, financial and product sectors.  Continue Reading

• Data mesh helping fuel Sloan Kettering's cancer research

  The cancer hospital and research center began using tools from data management vendor Dremio two years ago to decentralize its data operations and improve speed-to-insight.  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

• Peloton rides, runs, rows with AWS for data management

  The connected fitness company has long used AWS tools. When its data volume surged during COVID-19, Redshift was critical -- and still is as the company attempts a fiscal comeback.  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

• Essential skills for data-centric developers

  To become more data-driven, organizations need data-centric developers. Developers can learn a mix of technical and interpersonal skills to be an attractive candidate for the job.  Continue Reading

• Data steward responsibilities fill data quality role

  Data stewards tie together data operations. From quality to governance to boosting collaboration, data stewards are valuable members of any data effort.  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

• 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 management trends: Convergence and more money

  The past year focused heavily on data intelligence, lakehouse development and observability as vendors innovated to help enterprises make effective use of converged data and technologies.  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

• 16 top data governance tools to know about in 2023

  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

• 18 top big data tools and technologies to know about in 2023

  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

• 18 top data catalog software tools to consider using in 2023

  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

• Top trends in big data for 2023 and beyond

  Big data is driving changes in how organizations process, store and analyze data. The benefits are spurring even more innovation. Here are four big trends.  Continue Reading

• Data forecast for 2023: Time to extract more value

  Expect more organizations to optimize data usage to drive decision intelligence and operations in 2023, as the new year will be one of economic challenges for many.  Continue Reading

• 8 data integration challenges and how to overcome them

  These eight challenges complicate efforts to integrate data for operational and analytics uses. Here's why, plus advice on how to deal with them.  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

• Disney improves data integration efficiency with AWS Glue

  During the pandemic, Disney revamped its data integration process after the media and entertainment giant's existing data integration tools proved unable to meet its new needs.  Continue Reading

• What is a data warehouse analyst?

  Data warehouse analysts help organizations manage the repositories of analytics data and use them effectively. Here's a look at the role and its responsibilities.  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

• How to reap the benefits of data integration, step by step

  A new book lays out a strong case for data integration and guides readers in how to carry out this essential process.  Continue Reading

• How Lufthansa is flying its data warehouse to the cloud

  Moving from an on-premises data system to the cloud can be a complex operation. Lufthansa is looking to remove some of the complexity with virtualization.  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

• Should you run your database on premises or in the cloud?

  Use of cloud databases is surging, but there are still reasons for on-premises ones. Here's a comparison of cloud and local database architectures to help you choose.  Continue Reading

• A look at Presto, Trino SQL query engines

  The co-creator of the open source project at Facebook reflects on 10 years of growth as he helps lead one of its resulting tools into the future.  Continue Reading

• Understanding the benefits of a data quality strategy

  A data quality strategy can improve an organization's ability to generate value from data, but determining quality depends on the processes and use cases.  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

• 8 proactive steps to improve data quality

  Here are eight steps to take to improve your organization's data quality in a proactive way, before data errors and other issues cause business problems.  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

• What a big data strategy includes and how to build one

  Companies analyze stores of big data to improve how they operate. But those efforts will bring diminishing returns without a big data strategy. Here's how to build one.  Continue Reading

• MetLife improves efficiency with Tibco Data Virtualization

  The insurance giant's investment management division has reduced its data integration process from weeks to hours since adopting the analytics vendor's technology in 2017.  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

• How big data collection works: Process, challenges, techniques

  Taming large amounts of data from multiple sources and deriving the greatest value to ensure trusted business decisions hinge on a foolproof system for collecting big data.  Continue Reading

• Self-service data preparation: What it is and how it helps users

  Using self-service tools to properly prepare data simplifies analytics and visualization tasks for business users and speeds complex modeling processes for data scientists.  Continue Reading

• NLP and AI boost the automated data warehouse

  Businesses are working to automate as many elements of their data warehouses as they can through nascent tools like augmented analytics and natural language processing.  Continue Reading

• Data access key to Regeneron's innovation efforts

  After developing a COVID-19 treatment in mere months, Regeneron adopted a data catalog and is developing a data governance framework to speed up its drug development pipeline.  Continue Reading

• Hudi powering data lake efforts at Walmart and Disney+ Hotstar

  An open source cloud data lake platform is finding adoption at large organizations including Uber, Walmart and Disney+ Hotstar as the demands of data scale grow.  Continue Reading

• 'Building the Data Lakehouse' explores next-gen architecture

  This book excerpt by 'father of the data warehouse' Bill Inmon and experts Mary Levins and Ranjeet Srivastava explores the latest methods for wrangling data into usable intel.  Continue Reading

• Western Union looks to improve data quality with Talend

  Thomas Mazzaferro, chief data officer at Western Union, outlines the financial services company's approach to cloud data migration and how Talend fits into the data architecture.  Continue Reading

• Data forecast for 2022: Data quality and cloud convergence

  Expect data quality to be a top area of investment and activity next year as the need to trust data for operations, insight and machine learning will only continue to grow.  Continue Reading

• Data management trends in 2021: More money, more cloud

  In 2021, interest in the cloud data lakehouse model helped to propel multiple vendors forward as new serverless database-as-a-service systems emerged as well.  Continue Reading

• How DataOps can improve healthcare outcomes

  DataOps is more than just DevOps for data. It's a set of data orchestration, operations and management tools and principles that help organizations improve data pipelines.  Continue Reading

• How VMware's CDO views data management

  The chief data officer of the virtualization vendor details her views on the increasing challenges of dealing with growing volumes of data and the critical importance of data governance.  Continue Reading

• How to choose exactly the right data story for your audience

  A data practitioner has two jobs: tell the right data story and in the right way to win over project stakeholders, data expert Larry Burns says in his latest book.  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

• MongoDB CTO's view of data challenges

  The database vendor CTO discusses cloud migration, organizational structure and collaboration, go-to-market challenges organizations face, and the value of a chief data officer.  Continue Reading

• Why City Furniture embraced data virtualization

  With data coming from on-premises and cloud sources and spanning legacy systems, databases and even flat files, City Furniture faced problems bringing all its data together.  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

• 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

• Meltano spins out from GitLab to advance DataOps platform

  Douwe Maan, founder and CEO of Meltano, outlines the new data startup's approach as it raises seed funding to advance an open source ELT system.  Continue Reading

• EY CTO outlines data governance challenges

  Multinational professional services firm EY has taken a strategic view of how to manage and use data in a federated approach powered by a trusted data fabric.  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

• Healthcare device maker boosts production with data quality

  One of the world's biggest ventilator manufacturers ramped up production during the pandemic by improving its own data health to better understand and optimize operations.  Continue Reading

• The enterprise advantages of automated data collection

  Many organizations still rely on manual data entry that wastes time and results in low-quality data. Here are the latest automated data collection techniques and their benefits.  Continue Reading

• How automated metadata management improves business insights

  Automating metadata management can cut down time spent on tasks such as data tagging and cataloging. Explore how automated metadata management is improving data quality.  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

• Building a big data architecture: Core components, best practices

  To process the infinite volume and variety of data collected from multiple sources, most enterprises need to get with the program and build a multilayered big data architecture.  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

• Establish big data integration techniques and best practices

  A big data integration strategy departs from traditional techniques, embraces several data processes working together and accounts for the volume, variety and velocity of data.  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

• Pandemic triggered data security movement to DBaaS

  Database-as-a-service technology has aided enterprises tasked with keeping data secure with IT professionals working from home during the COVID-19 pandemic.  Continue Reading

• Who belongs on a high-performance data governance team?

  Putting together a high-quality data governance team can be a challenge. Explore the necessary team members and best practices for a high-performing team.  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

• Vaccination data poses data management challenges for firms

  If companies are considering the use of vaccination credentials to reopen offices, IT teams should start planning now.  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

• How a DataOps pipeline can support your data

  DataOps has created a lot of hype as a data management pipeline because of its focus on collaboration and flexibility. Read on to find out how these priorities support your data.  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

• Open source database migration guide: How to transition

  Open source database transitions have been on the rise as they prove to be worthy competitors to commercial database options, but that transition requires strategy and user buy-in.  Continue Reading

• AWS Data Exchange and the third-party cloud data marketplace

  The general manager of the AWS Data Exchange data feed service details what the cloud data marketplace is all about and where it's headed in the future.  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

• Why your data story matters and how to tell it

  Data storytelling isn't just for business analysts. Find out how to build a data management story and why you need to have one in the first place.  Continue Reading

• Cloud data catalog benefits for the enterprise

  Vendor cloud data catalog options are expanding and offering more automated tools to end users. Read on to find out how enterprises can benefit from these options.  Continue Reading

• Talend CEO talks about vendor's growth strategy

  With its cloud business a primary driver of growth, Talend is progressing toward the goal of increasing annual revenue from $250 million to $1 billion.  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

• Pandemic exposes difficulty of data management in education

  Limited resources and a shift to remote learning have shown the inequalities across school districts when it comes to data management and the negative impact this can have.  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

• Graph database vs. relational database: Key differences

  Relational databases and graph databases both focus on the relationships between data but not in the same ways. Here are some key differences between the two.  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

• How Alation builds on data catalog for data intelligence

  Aaron Kalb, co-founder and Chief Data and Analytics Officer (CDAO) of Alation, provides insight into the evolution of his company's technology to embrace data governance that enables data intelligence for organizations to fully benefit from their ...  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

• Emerging data management trends to watch in 2021

  A number of nascent efforts across the enterprise data landscape became manifest in 2020 that are likely to become larger trends into 2021, including the data lakehouse, Iceberg and Presto.  Continue Reading

• ChaosSearch looks to bring order to data lakes

  Data lakes are like junk drawers in the sky, but new tech from ChaosSearch organizes the mess and makes it searchable. Here, CEO Ed Walsh shares the details and what's next in 2021.  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

• Data anonymization best practices protect sensitive data

  See how data anonymization best practices can help your organization protect sensitive data and those who could be at risk if that data identified them.  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

• Collibra grows enterprise data governance for the cloud

  Collibra CEO discusses the importance of data governance for enterprises and how to tie data governance to business terminology to go beyond simply controlling data.  Continue Reading

• Top 5 U.S. open data use cases from federal data sets

  The U.S. government has made data sets from many federal agencies available for public access to use and analyze. Check out some of the ways that data is being used.  Continue Reading