Features

Features

Data quality techniques and best practices

• 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

• 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

• How to navigate the challenges of the data modeling process

  Data modeling and curation can help businesses more efficiently use data they've collected. There are challenges, however -- beginning with ensuring data quality.  Continue Reading

• 8 tips to improve the data curation process

  A data curation and modeling strategy can ensure accuracy and enhance governance. Experts offer eight best practices for curating data. First, start at the source.  Continue Reading

• How to manage data and the GDPR right to be forgotten

  The General Data Protection Regulation requires organizations to delete personally identifiable information if customers ask -- which can be a challenge. Experts offer four tips.  Continue Reading

• 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