Documenting Data Lineage : Connecting Business Meaning To Technical Implementation

Categories: Metadata Governance
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About Course

Data lineage becomes useful when business meaning, logical structures, technical implementation, and supporting evidence connect.
This course shows how Data Governance professionals and Data Stewards can document lineage across application, conceptual, logical, physical, and vertical levels. You will work with application flows, business and data domains, concepts and rules, source-to-target mappings, technical lineage validation, and cross-layer traceability.
Practical XYZ Company exercises and reusable templates help you turn fragmented lineage information into documented, validated, and maintainable evidence.

What Will You Learn?

  • Scope data lineage at the right level.
  • Map application flows across business and data domains.
  • Translate business meaning into reusable logical lineage.
  • Document source-to-target mappings and transformation logic.
  • Validate technical lineage using business evidence.
  • Connect and maintain lineage across metadata layers.

Course Content

Data Lineage at Multiple Levels
This topic establishes how data lineage is scoped across multiple abstraction levels. Participants work with the lineage metamodel and examine how business, conceptual, logical, physical, and vertical views relate. The focus is on choosing the appropriate level for a lineage question and understanding where Data Governance professionals and Data Stewards contribute through documentation and validation before detailed lineage work begins.

  • Scoping Data Lineage
    03:51

Data Lineage at the Business Level
This topic moves lineage into the application landscape and establishes its business context. Participants examine how application flows cross business and data domains and why both perspectives are needed for scoping. Ownership and stewardship are connected to the relevant flows while the view remains intentionally high-level, creating a practical basis for later documentation of tables, columns, mappings, and transformations.

Data Lineage at the Conceptual Level
This topic focuses on documenting data lineage independently of individual applications. It examines how business concepts, definitions, relationships, and rules provide the foundation for reusable logical data requirements. You will explore how information from concept maps, semantic models, and business glossaries contributes to lineage documentation. The topic also explains how calculated business results are connected to their input concepts and governing rules before technical implementation is considered.

Data Lineage at the Logical Level
This topic examines how logical data lineage is documented within a selected application chain. It connects the business meaning established earlier with actual input and output structures and the transformations between them. You will explore source-to-target mappings and the information required to explain conversions, aggregations, and calculations. The topic also shows how business validation questions help verify that implemented transformations preserve the intended meaning.

Data Lineage at the Physical Level
This topic examines how technical data lineage is validated against business expectations. It explains the limitations of automated lineage discovery and the need to compare technical findings with business lineage, documentation, and practical business knowledge. You will explore how these comparisons reveal missing relationships, incorrect calculations, and incomplete evidence. The topic also introduces validation decisions and the information required to document corrections and assign follow-up actions.

Vertical Data Lineage
This topic explores how business meaning is connected to technical implementation across metadata layers. It examines the relationships between conceptual objects, logical attributes, and physical tables and columns. You will learn why vertical connections require explicit matching rules and supporting evidence rather than similar object names. The topic also covers common traceability gaps and the actions needed to resolve missing representations, incorrect rules, or unclear validation responsibilities.

Data Lineage Maintenance
This topic examines how data lineage documentation is maintained as business and technical environments change. It distinguishes maintenance triggered by specific events from periodic reviews based on lineage criticality and change frequency. You will explore how changes to rules, applications, and transformations affect multiple lineage artefacts. The topic also explains the maintenance process, from identifying a change and assessing its impact to updating, validating, and closing the affected lineage records.

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