01
Sources & definitions
Trace the inputs, transformations, and business meaning behind the data people use.
Typical outputs
- A source-to-output data-flow map
- Shared metric definitions and ownership notes
ServicesData & analytics
06 / Data & analytics
Know where your numbers come from.
Connect data sources, shared definitions, and quality checks so reporting has a foundation your team can understand.
Discuss data & analytics
Where we can help
Follow the number back to its source.
When a report changes, the team needs to know whether the business changed, the inputs changed, or the pipeline failed. We work through that path, from source and transformation to the people using the output.
A useful starting point when…
- Teams report different values for the same measure.
- Data moves through manual exports or fragile integrations.
- Quality issues are found after the report has been used.
Scope & deliverables
What the work
What the work
can produce.
These are possible areas of work. Your scope will name the outputs and acceptance checks we agree together.
02
Pipelines & integration
Build repeatable paths between source systems and the agreed reporting or operating outputs.
Typical outputs
- Pipeline and transformation code
- Run configuration and failure-handling guidance
03
Quality & validation
Put checks at useful points in the flow so missing, inconsistent, or unexpected data can be identified.
Typical outputs
- Data-quality rules and validation checks
- Exception handling and review procedures
04
Reporting & handoff
Make the output understandable alongside its definitions, freshness, and known limits.
Typical outputs
- Reporting views for the agreed questions
- Lineage notes and an operating walkthrough