ETL Mapping Template for Data Pipeline Projects
A practical template for documenting source-to-target mappings, transformation rules, validation checks and ownership in ETL and ELT projects.
Use this template when migrating reporting systems, building data pipelines, connecting ERP or CRM data, or preparing a governed data model for Business Intelligence.
Why it matters
ETL projects become risky when transformation rules live only in conversations.
A clear mapping template helps teams align business meaning, technical fields, transformation rules, validation checks and target models before pipeline development starts.
Business users cannot trace dashboard numbers back to source fields.
Transformation rules are understood by a few people but not documented.
Migration projects rely on spreadsheets without clear validation ownership.
Data quality issues are discovered late during dashboard testing.
Resource structure
What the template covers
The template structures mapping work so business, data and technical teams can work from the same source of truth.
Source system inventory
Identify where the data comes from and what each source represents.
- Document source application, table, file or API
- Capture source field name, data type and business description
- Identify owner and refresh frequency
Transformation logic
Define how raw data becomes usable business data.
- Document joins, filters, exclusions and derived fields
- Define code mappings, status rules and date logic
- Capture currency, unit and format transformations
Target model and BI usage
Connect technical mapping to reporting and analytical outcomes.
- Define target table, field and semantic meaning
- Link fields to KPIs, dimensions or report visuals
- Identify aggregation and granularity rules
Validation and governance
Make the pipeline testable and maintainable.
- Define reconciliation checks and expected totals
- Document test cases and acceptance criteria
- Assign ownership for corrections and future changes
Related Datilog expertise
Continue from preparation to implementation.
This resource is designed to help your team clarify the project. Datilog can then support architecture, delivery, automation and governance.
Next step
Turn this resource into a practical roadmap.
Share your current context and Datilog can help identify the highest-value actions for your data, cloud or workflow automation initiative.