des-sprint-planning

Sprint planning for data engineering requires mapping story dependencies before selection. You build a candidate pool from your story catalog, apply capacity limits, and group stories by release while preserving prerequisite order to prevent blocked implementation workflows.

A readiness check in sprint planning validates whether stories meet the Definition of Ready before commitment. It assesses story availability, workflow status, and dependency resolution to ensure selected backlog items can actually be executed within the sprint timeframe.

When capacity is unknown, sprint selection uses guided handling to prioritize committed stories while tagging others as stretch or deferred. Goal-first scoping ensures the candidate pool aligns with the sprint objective even without precise capacity assumptions.

Release grouping during backlog selection organizes stories into logical deployment batches within the sprint plan. This ensures dependency ordering respects both sprint-level prerequisites and broader release boundaries defined in your epic and story catalogs.

Generating a sprint plan requires an epic catalog and story catalog as mandatory inputs. Optional workflow status data enhances dependency ordering, and the output is a fully specified sprint-plan artifact containing DoR, DoD, risks, and readiness checks.

Dependency ordering explicitly handles blocked and unblocked work rules by categorizing stories accordingly during selection. Blocked stories are flagged in the sprint plan artifact, ensuring they are excluded from committed capacity until their prerequisites are resolved.