Realizing the potential of clean mastered data for businesses

DataOps is an automated, process-oriented methodology, used by analytic and data teams, to improve the quality and reduce the cycle time of data analytics. What does that mean in terms of benefits? Data-driven aspects of the business can respond rapidly…

Michael Stonebraker’s work and contributions to the concepts and practices underlying modern database systems are truly remarkable. I’ve followed Mike’s accomplishments for decades, and have worked closely with him for the past six years—one of the highlights of my career.…

The kind of broad data unification that Tamr does typically leads to complex deployments that involve many steps across many systems. This type of unification requires a reliable, manageable way to automate and coordinate all of this activity while supporting…

Data variety has been the Achilles’ heel of enterprise BI and analytics projects since long before the three V model of Big Data brought it into the spotlight (along with its siblings ‘volume’ and ‘velocity’). Over the past 20 years,…

There is a long-standing debate about appropriateness of traditional RDBMS and NoSQL systems for different applications. One motivation for a non-RDBMS storage tier for an application is data flexibility. The conventional wisdom about applications like Tamr’s that work with a…

  Among Big Data challenges, Variety is the hardest to deal with through automation. Variety comes in the form of incompatible data formats, non-aligned data structures, and inconsistent data semantics. These are not merely a consequence of insufficient standards: although…