Data lineage

SQLink is the Data Lineage Monitoring Platform, an independently deployable and licensed product. It provides lineage spaces, parsing tasks, maps, application scenarios, manual lineage, impact analysis, and root cause analysis. It can extend DAM's lineage capabilities; basic lineage viewing from metadata objects remains part of Metadata Management.

Product boundaries

Basic metadata lineage starts from tables, fields, and reports. SQLink's advanced features require the separate SQLINK license. Connectivity, synchronization, and navigation between DAM and SQLink depend on deployment. Similar views do not imply automatic data synchronization.

Key concepts

Term	Meaning
Lineage space	Workspace for source resources, files, parsing tasks, and results; not a database
Namespace	Identity scope distinguishing objects with the same name across systems or environments
Parsing task	Extracts processing and dependency relationships from scripts or task files and produces a report
Lineage map	Graph exploration with direction, level, depth, and filters
Application scenario	A persistent object and relationship scope for monitoring, change impact, or structural quality analysis

See spaces, tasks and reports, lineage views, and scenarios. Harvested metadata alone does not establish accurate lineage.

Users and entry points

User	Tasks	Entry points
Lineage consumer	Search objects, inspect dependencies, assess changes	Data Catalog, Lineage Map, Application Scenarios
Data developer	Parse SQL and inspect transformations	SQL Lineage, Lineage Map
Lineage administrator	Harvest metadata, parse files, manage namespaces	System Management, Lineage Management, Task Management

Plan namespaces and harvest metadata first, build and validate lineage next, then enable exploration and analysis.

Guides

• Quick start: scope, initialize, harvest, validate, and analyze.
• Explore lineage: discover objects through the catalog and map.
• View and analyze lineage: direction, levels, depth, filters, exports, and comparisons.
• Application scenarios: monitoring, impact, and structural quality.
• Online SQL lineage: immediate SQL analysis.
• Administration: resources, namespaces, preprocessing, and scheduling.
• Lineage spaces: organize database, report, OpenLineage, and file resources.
• Harvest and synchronize resources and parsing tasks.
• Namespaces and preprocessing and manual lineage.
• Integration reference: boundaries and API examples.
• Deployment preparation: components, configuration, and acceptance.