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“Someone who knows SQL can now generate a classification or regression prediction directly against tables already in BigQuery, using the two new functions, without training, tuning, or deploying a model first, and without moving data out to a separate ML platform, which also simplifies governance and cuts the infrastructure cost of running a parallel platform,” Jena explained.
That, according to Manoj Chandra Jha, principal analyst at Nord-IQ Research, translates to TabFM collapsing the traditional multi-persona workflow, stretching from an analyst, a data scientist, and a ML engineer, into a single SQL call, thereby potentially reducing headcount requirements.
But benefits may vary by workload
However, the new model has limitations that enterprises should be aware of before replacing conventional ML workflows.
