Features

Features

Data quality techniques and best practices

• Data integrity protection spurs greater security spending

  As hacking, ransomware and malware attacks mount, companies place big data protection and integrity among the primary reasons for increased spending on security software.  Continue Reading

• Information architecture applied to big data streaming, AI

  New technologies challenge data professionals, but taking a step back helps with hurdles. In this interview, consultant William McKnight takes a measured look at data streaming, GDPR and AI.  Continue Reading

• Cloud workloads, data lakes challenge information architecture

  Data management options are expanding; cloud workloads are an example. That means changing your approach to information architecture, says data management expert William McKnight.  Continue Reading

• DMBOK2 eyes evolving data management best practices, challenges

  In a Q&A, DAMA president Sue Geuens talks about the second edition of the group's DMBOK reference book and how data management trends and processes have changed since the first version.  Continue Reading

• Data monetization takes three routes to turn data into dollars

  Data monetization is not monolithic. Instead, it takes several forms, according to MIT researcher Barbara Wixom. Each approach has its own unique traits.  Continue Reading

• Data lake management, governance a hands-on job for big data teams

  Deploying big data systems is just the first step for IT and data management teams. The next big challenge is setting up systems and processes for governing data lakes.  Continue Reading

• Big data queries eyed to head off Hadoop performance problems

  Processing in big data systems can slow to a crawl if queries are not properly tuned or workloads not well balanced -- issues that call for careful monitoring of clusters.  Continue Reading

• Hadoop data governance takes hold in companies as data gets 'bigger'

  LinkedIn, Cleveland Clinic and fitness company Beachbody are examples of organizations that have increased their data governance efforts in connection with big data applications.  Continue Reading

• Q&A: Big data leads to bad insights without a data governance plan

  Big data holds the potential to provide invaluable insights for business growth, but only if data governance is part of the plan.  Continue Reading

• Inside the Informatica Master Data Management portfolio

  Informatica Master Data Management is aimed at helping sales, marketing and customer service teams ensure they're working from the most relevant and accurate data available.  Continue Reading

• Examining the top data governance tools on the market

  Expert John Ladley examines the leading data governance software products, comparing and contrasting their features to help you determine which tool will best meet your needs.  Continue Reading

• How to narrow down your choices for buying a data governance tool

  Evaluating and selecting a data governance tool depends on not only features and functionality, but also how you will use the tool to add value to your organization.  Continue Reading

• How to know if your company is ready for data governance tools

  Even if you can identify with the use cases presented here, it's important your organization is well-prepared to deploy the software it buys.  Continue Reading

• How data governance software helps ensure the integrity of your data

  While a data governance initiative comprises people, processes and technology, data governance software supplements and automates the processes the organization implements.  Continue Reading

• How to identify master data in a multi-domain MDM program

  In an excerpt from their book on managing multi-domain master data management programs, Mark Allen and Dalton Cervo explain how to identify MDM domains and your master data.  Continue Reading