The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. It is also a sound strategy when experimenting with several parameters at the same time. And sometimes even if it is not[1].)

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Octopai

MAY 2, 2022

Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. Issue detected?

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

Alation

SEPTEMBER 28, 2022

DataOps as a term was brought to media attention by Lenny Liebmannin 2014, then popularized by several other thought leaders. DataOps strategies share these common elements: Collaboration among data professionals and business stakeholders. Over the past 5 years, there has been a steady increase in interest in DataOps. Simplicity.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation.

Statistics 44

Statistics Optimization Modeling Experimentation 44