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Uncertainties: Statistical, Representational, Interventional

The Unofficial Google Data Science Blog

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

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. Crucially, it takes into account the uncertainty inherent in our experiments.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. Commonly used models include: Statistical models. Dashboards and other user interfaces that allow users to interact with and view results.

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Three Emerging Analytics Products Derived from Value-driven Data Innovation and Insights Discovery in the Enterprise

Rocket-Powered Data Science

This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative. I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications.

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Systems Thinking and Data Science: a partnership or a competition?

Jen Stirrup

Therefore, interacting with systems using minimal technical skills is very beneficial. From a data science perspective, it is possible to begin immediately by framing problems regarding machine learning or statistical issues. How is it possible to enable data-driven decisions in a systems thinking approach?

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. The AGI would need to handle uncertainty and make decisions with incomplete information. NLP techniques help them parse the nuances of human language, including grammar, syntax and context.

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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.