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The pandemic pivot: 5 key leadership lessons that will last

CIO Business Intelligence

The early days of the pandemic taught organizations like Avery Dennison the power of agility and experimentation. Paper-based finance processes have been replaced with automated workflows, and internal reviews of business investments, which used to be a hard copy-based process, have also been automated.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. However, it is far from perfect, since it certainly does not have reasoning skills, and it also loses its “train of thought” after several paragraphs (e.g.,

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Variance and significance in large-scale online services

The Unofficial Google Data Science Blog

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.