Features

Features

• Maintaining data integrity key for data quality

  Maintaining data integrity through improved communication and data literacy is paramount for organizations in the enterprise seeking to ensure data quality and trust.  Continue Reading

• Why understanding data structures is so important to coders

  Jay Wengrow talks about how his new book on data structures and algorithms and considerations for making your choices as efficient as possible.  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

• Key steps in the feature engineering process

  Feature engineering is key to machine learning algorithms. Read on to learn how those features are created and chosen to increase the accuracy of those models.  Continue Reading

• Talend evolves enterprise data integration efforts

  The CTO of Talend outlines the path the data integration vendor has taken in recent years as the market for big data has evolved along with the need to treat data as an asset.  Continue Reading

• The evolving role of the chief data officer

  The job of the chief data officer is expanding to be more strategic as the need for organizations to connect and make sense of vast sums of data continues to grow.  Continue Reading

• Data mapping as a service, a modern form of data discovery

  The CEO of ActiveNav provides insight into how data mapping fits into the data management landscape as the vendor launches a new data mapping-as-a-service platform.  Continue Reading

• Reltio sets new course for master data management strategy

  The founder of data management firm Reltio provides insight into the evolving nature of master data management, as organizations look to get a more complete view of their data.  Continue Reading

• Top 3 data privacy challenges and how to address them

  There are many issues enterprises face in their data privacy programs. Read on for how to address the most common three found across organizations.  Continue Reading

• Investment in talent key for data quality in healthcare

  Investing in training employees on proper data gathering and management practices is crucial for healthcare organizations seeking to ensuring data quality and patient care.  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

• Informatica CEO outlines digital transformation challenges

  Informatica chief Amit Walia gives insight into what organizations need most to enable digital transformation and why enterprise data management is at the foundation.  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

• How Riot Games upped its enterprise data governance game

  Data governance product manager at Riot Games details how the game vendor dealt with data ownership challenges by embracing new processes and technologies for data management.  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

• 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

• Top 5 feature engineering tips for better models

  From understanding a model's expected goal to factoring in subject matter expertise, experts talk about the best ways to improve your feature engineering.  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 points for a monitoring center pandemic action plan

  On-site monitoring centers come under stress when it's necessary for most workers to telecommute. Here are key points to include in a crisis plan to continue service availability.  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

• Surprising insight on the data governance process

  Many enterprise data governance processes have been around for a while. Read on for ways a modern approach can be beneficial, and preview a new book that can update your 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

• Yellowbrick CEO outlines hybrid path to cloud data warehouse

  Neil Carson, co-founder and CEO of Yellowbrick, details the state of data warehouse market and outlines use cases for hybrid on-premises and cloud deployments.  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

• Data growth spawns enterprise data management system challenges

  Enterprises are creating and using more data and storing more of it in the cloud. If they use that data strategically, they can improve business outcomes.  Continue Reading

• Organization and automation ease data preparation process

  By laying down proper groundwork and investing in automated checks, companies can ease the data preparation process and ensure they are getting the most out of their data.  Continue Reading

• GDPR, CCPA, cloud drive security management tool makeovers

  As data protection and privacy laws like GDPR and CCPA take hold, data managers refine governance practices, while vendors enhance traditional big data security tools.  Continue Reading

• Improving enterprise data governance with data trust

  Talend users from Covanta and AutoZone provide insight into data management challenges amid growing data complexity at the Talend Connect virtual conference.  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

• Instaclustr CTO on open source database as a service

  Ben Bromhead, co-founder and CTO of Instaclustr, provides insight into the state of the open source database-as-a-service market as COVID-19 changes priorities and traffic flows.  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

• Building a strong data analytics platform architecture

  A strong analytics platform is key to meeting demands in a data-driven business. Read on for the key components your platform architecture should include.  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

• How to ensure your data lake security

  Your data lake is full of sensitive information and securing that data is a top priority. These are the best practices to keep that information safe from hackers.  Continue Reading

• How a logical data fabric can improve data management

  As data continues to grow across different sources, speakers at the Fast Data Strategy virtual summit outline how a logical data fabric approach can help.  Continue Reading

• Building a database application the DIY way

  Business users experience the trials, tribulations and exultations of building a DIY DBMS, especially when IT expertise is not readily available or costs are too high.  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

• Data governance and COVID-19 data security challenges

  Maintaining data governance and data security best practices is essential now more than ever. But the increase in working from home can put a strain on those practices.  Continue Reading

• How the GraphQL Foundation is enabling data graphs

  The GraphQL Foundation has grown over the course of its first year as database and application developers adopt the API layer approach to connecting different data sources.  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

• Common data lake challenges and how to overcome them

  Managing the data contained in your enterprise data lake presents many challenges. From the amount of data to data inconsistencies, here are some solutions to common issues.  Continue Reading

• Chief data officer role advances enterprise data governance

  With organizations of all sizes coping with the impact of COVID-19, the importance of enterprise data governance and chief data officers is coming into sharper focus.  Continue Reading

• The business benefits of enterprise data governance and MDM

  Data leaders from prominent large organizations provide insights into data governance best practices and benefits, at Informatica's MDM 360 and Data Governance virtual conference.  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

• How to build an effective streaming data architecture

  Data architecture can be tricky when it comes to real-time analytics. Clear objectives and scalability are important factors when determining the streaming data architecture you need.  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

• 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

• Breaking down data silos with strong data governance

  Not having a single source of truth can be a huge issue for data professionals. But strong data governance policies can prevent data silos and lead to better-quality data.  Continue Reading

• Where InfluxDB time series database is going

  Users need more than SQL for querying databases, according to Paul Dix, co-founder and CTO of InfluxData. That's why the vendor created the Flux data scripting and query language.  Continue Reading

• Analytics demands add loftier goals to data warehouse strategies

  As the concept of storing data and the technologies needed to do it evolve, companies with set goals in mind are building their data warehouses to maximize analytics outcomes.  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

• NuoDB set to improve distributed SQL performance

  Ariff Kassam, CTO of distributed SQL database vendor NuoDB, outlines how his company has embraced cloud native and hints about what's to come in the year ahead.  Continue Reading

• How to improve data governance for self-service analytics

  Citizen data scientists and self-service analytics are on the rise as the data scientist shortage continues. Here are some data management best practices to support them.  Continue Reading

• Q&A: The challenges of cloud-native data management

  Cloud native data management isn't usually the first thing on anyone's mind, acknowledges Portworx co-founder and CTO Goutham Rao -- but find out how it's become part of organizations' journey.  Continue Reading

• Data catalog management for analytics fraught with unique demands

  Data catalogs for analytics applications demand detailed assessment of user needs, cross-functional teams, ready access, continuous improvement and a self-sustaining system.  Continue Reading

• How to streamline feature engineering for machine learning

  Structured data is necessary in machine learning, but sifting through data is time consuming. Streamlining the feature engineering process can help data scientists be more productive.  Continue Reading

• Top database cloud migration considerations for enterprises

  Many organizations are switching to cloud databases and big data platforms. But understanding what option best meets your data needs is an important first step.  Continue Reading

• Oracle looks to grow multi-model database features

  Decade after decade, Oracle continues to be relevant in the database market as it pivots to include an expanding list of capabilities to serve users, notably cloud.  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

• Managing unstructured data is crucial to enterprises' AI goals

  Unstructured data makes up a huge portion of most businesses' data volume. But, with data-hungry AI systems coming online, making sense of these stores has never been more important.  Continue Reading

• Data silos and culture lead to data transformation challenges

  Data continues to grow at a rapid rate, and users are faced with increasing complexity and challenges to make sense of it all in a way that helps improve business outcomes.  Continue Reading

• How enterprises navigate GDPR data management rules

  For businesses that operate in the EU, complying with GDPR has to be a top priority. And in many, much of the compliance burden falls on the data management staff.  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

• DOD CDO shares 7 data management best practices

  The DOD's first chief data officer, Michael Conlin, shares tips on how organizations can modernize their data management practices with the objective of matching private enterprise.  Continue Reading

• Align business and IT drivers through data quality best practices

  Information management consultants talk about the importance of aligning business and IT drivers for a holistic architectural approach to ensuring strong data quality.  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

• How big tech breakup would affect the tech industry

  Breaking up the tech giants would be difficult and might create initial chaos in market, help smaller competitors and potentially raise prices for enterprises.  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

• Enterprise data marketplace aims to ease self-service chaos

  Self-service data preparation can duplicate work and slow down analytics. One possible fix: an internal marketplace where users can 'shop' for data assets.  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

• Information Builders exec talks data management ethics

  In this Q&A, James Cotton, director of the Data Management Centre of Excellence at Information Builders, offers advice on how organizations can carry out ethical data management.  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

• 11 real-time data streaming roadblocks and how to overcome them

  Experts detail common challenges that IT teams encounter when deploying and managing real-time data streaming platforms and offer advice on how to address them.  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

• Using a LEFT OUTER JOIN vs. RIGHT OUTER JOIN in SQL

  In this book excerpt, you'll learn LEFT OUTER JOIN vs. RIGHT OUTER JOIN techniques and find various examples for creating SQL queries that incorporate OUTER JOINs.  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

• Data modeling techniques to overcome common business challenges

  In this interview, author and data modeling instructor Steve Hoberman discusses techniques for dealing with challenges that may arise in the data modeling process.  Continue Reading

• How 4 organizations are breaking down data silos

  Siloed data continues to inhibit enterprise efficiency. Here, IT professionals discuss problems their organizations are facing around data silos -- and how they're solving them.  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 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 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 virtualization layer feeds logical data warehouse, Agile BI

  Indiana University is using data virtualization to combine data from various source systems for analysis, as part of an initiative to improve strategic decision-making.  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

• Data model design tips to help standardize business data

  Data models should be understandable to business users and kept to a reasonable scope, say the leaders of a data modeling initiative at England's Environment Agency.  Continue Reading

• Wayfair charts open source components course to growth

  Teams at Wayfair mix new open source tools to power customer-facing apps. In such shops, tech leaders like Ben Clark must deftly maneuver an obstacle course of data components.  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

• USAA adds data engineering skills to speed data science work

  When the United Services Automobile Association's data science team wasn't getting data in the right format, the team lead realized the USAA needed more data engineers.  Continue Reading