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Demonstrate how to leverage PL/Python and the GreenplumPython library to push data transformation logic directly into the Greenplum Database. This approach aligns with a key best practice in big data architecture: move processing to the data, not the other way around. Achieve a scalable, more secure, more cost effective solution for your Python dev team.
This blog summarizes a demonstration delivered to a customer interested in understanding how Greenplum can be used for machine learning, without exporting data to external systems. The objective was to showcase how churn modeling can be prototyped and iterated entirely within Greenplum using the gpmlbot utility, which automates feature preparation, model training, and evaluation.