Data Quality is one of those things that we don't pay attention to until it comes and bites us, and when it does, its usually a customer that notices it. As always, the poor beleaguered dev/database guys pay the price and work long hours and over the weekend to track things down and sort things out.
In the good old days we could rely on things like MS Data Quality Services to come to the rescue, however, now we operate in the cloud with a mixture of Vendor products, database types and at different scale, so what are the options open to us, especially on a limited budget?
This session will examine using basic Data Science and AI techniques along with open source solutions and tools, to help improve your data quality, no matter the format of the data and where it is stored. It will also demonstrate a new Open Source Data Validation/Quality toolkit Allen is developing that runs naively in the cloud for both data at rest and live streaming data at rest and live streaming data in moti
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