Google AI Blog: Machine Learning in Google BigQuery

Today we’re announcing BigQuery ML, a capability inside BigQuery that allows data scientists and analysts to build and deploy machine learning models on massive structured or semi-structured datasets. BigQuery ML is a set of simple SQL language extensions which enables users to utilize popular ML capabilities, performing predictive analytics like forecasting sales and creating customer segmentations right at the source, where they already store their data.

I'm really fascinated by this. My belief is that more and more types of data processing will be made accessible via SQL language extensions in this way. The modern cloud analytic databases are incredibly powerful and more and more companies are dumping their data in to allow interactive analysis for growing analyst teams whose toolsets are primarily driven by SQL. Those analysts want to use ML algorithms, but frequently the piping of data from a SQL environment to a Python environment and back again is too much of a barrier. Plus, all the data transport is inefficient.

This product launch itself is interesting in and of itself, but moreso because of what it portends for the future. My bet is that in a year this feature supports more than linear and logistic regression.


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