Business problem

Data Foundation & Governance

Landing ERP data in a lakehouse without losing deletes, history, or control of who reads it.

Every metric elsewhere in this library assumes the data underneath it is right, and that assumption is where large analytics investments usually fail. A hard delete in the source system leaves no row to notice, so a change-data-capture feed that only reads inserts and updates carries a deleted order forever. An inventory snapshot taken as a daily copy of the current on-hand cannot be restated once a backdated movement lands, so the history quietly disagrees with the ledger it came from. And a governed lakehouse that nobody can query is as unusable as an ungoverned one that everyone can. This domain is guide-led by design — there is no KPI to define and no dashboard to pattern, because the work is a set of decisions made once at the pipeline layer that every downstream number inherits. The guides cover them in the order they bite: what breaks when a source row disappears and how each ERP lets you detect it, which ingestion path preserves the history each source overwrites in place (and what the lakehouse must snapshot itself), which layer of a medallion pipeline owns each fix so a quirk is corrected once rather than per-report, the checks that catch a bad load before a dashboard does, and how Unity Catalog is laid out so governance is a property of the catalog rather than of a review meeting.