ds-executing-plans

Executing an analysis plan in verified batches involves running SQL and notebook tasks in controlled chunks, pausing for methodological review after each batch. This checkpointed execution produces reproducible artifacts with reader-facing pass/fail verification between runs.

Checkpointing prevents unreproducible notebook workflows by executing approved plans in small batches and producing review-ready evidence like manifests and diagnostic cells. It stops execution on methodological red flags instead of failing fast with scattered, noisy errors.

Adding runtime observability to long SQL queries requires inserting stage messages, timings, and row-count signals during batch execution. This coarse progress tracking ensures analytical work is not silent while avoiding noisy log spam during validation checks.

Scaling validation checks for experiment analytics is supported by applying the plan’s validation level—light, standard, or strict. This scales decision-protecting diagnostics appropriately to match the required rigor of the analytical artifacts being produced.

Generating rerun evidence for analysis execution is best handled by producing compact pass/fail artifacts like tables and manifests during checkpointed batches. This reader-facing verification replaces scattered fail-fast errors with reproducible diagnostic cells.