Enterprise Catalog
Enterprise Catalog - what the exam tests
This domain tests metadata discovery and cataloging: registering resources, scanning them, reading technical and business lineage, and making assets findable and trustworthy through glossary links, certification, ownership, and search facets.
Core rules
- A catalog is populated by scanners running against registered resources such as databases, files, BI tools, and cloud stores. Scanning extracts structure and metadata; it does not validate data values.
- Technical lineage is derived from parsed SQL and job logic down to column level; business lineage connects those columns to glossary terms, reports, or processes. Lineage depth depends on connector support and parseable logic.
- Assets carry metadata: description, owner, data domain, certification status, rating, and user tags. Similar-asset recommendations use CLAIRE-based similarity across metadata and usage patterns.
- Search combines keyword matching with facets such as resource type, domain, certification, and owner. The glossary provides the semantic bridge between business terms and physical names.
- Data domain discovery automatically identifies sensitive columns during scanning and feeds classification and governance.
Worked example
An analyst searches for customer revenue and finds no table with that name. Reasoning: the keyword matches a glossary term linked to FCT_ORDERS.AMT and to a Sales report. Following the term reveals column-level lineage from ORDERS through a staging table to the report. To make this dependable, link glossary terms only to certified assets - otherwise search surfaces stale, uncertified copies that analysts then trust.
Traps
- Expecting column lineage for stored procedures or dynamic SQL the parser cannot read.
- Assuming scanning profiles data quality; it reads metadata only.
- Certifying an asset without an owner or glossary link, which undermines trust signals.