DataOps as a Discipline

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…

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Making the Impossible Possible: the Tamr Journey

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.…

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Death by Data Variety: Two Decades Working On The Cure

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,…

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RDBMS vs. NoSQL: Data Flexibility

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…

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Taming the Hydra of Data Variety

  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…

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