Sat.Jun 25, 2016 - Fri.Jul 01, 2016

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To Balance or Not to Balance?

The Unofficial Google Data Science Blog

By IVAN DIAZ & JOSEPH KELLY Determining the causal effects of an action—which we call treatment—on an outcome of interest is at the heart of many data analysis efforts. In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. In observational studies treatment is assigned by nature, therefore its mechanism is unknown and needs to be estimated.

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Data Governance Frameworks are like Jigsaw Puzzles

Jim Harris

In a recent interview, Jill Dyché explained a common misconception, namely that a data governance framework is not a strategy. “Unlike other strategic initiatives that involve IT,” Jill explained, “data governance needs to be designed. The cultural factors, the workflow factors, the organizational structure, the ownership, the political factors, all need to be accounted for when you are designing a data governance roadmap.