Manual vs Automated Data Quality Processes

This chapter delves into the distinctions between manual data quality processes, which involve collecting requirements from end users and enforcing them, and automated data quality processes, which leverage tools like check assistance and GPT to enforce natural language checks. The chapter also highlights the importance of automating data quality for efficiency and the role of domain experts in driving data quality for downstream products.