PMLE - Collaborating Within and Across Teams to Manage Data and Models - Section 2.1

Explore and preprocess data for ML across tabular, text, and image types, choosing the right tool for scale such as BigQuery, Dataflow, Apache Spark, and in-memory Python frameworks, consolidating features in the Agent Platform Feature Store, and protecting personally identifiable information.

Choose between Dataflow, Apache Spark, and in-memory Python frameworks based on data volume and type, and consolidate reusable features in the Agent Platform Feature Store to avoid training-serving inconsistency. Recognise which PII-handling techniques - such as tokenisation and data masking - are appropriate when preprocessing sensitive tabular, text, or image data.

Examworthy is not affiliated with or endorsed by Google Cloud. Original, blueprint-aligned practice material only.