Analytics and reporting: build a shared answer to the business question

Start with a question someone needs to answer

A reporting project can collect many attractive charts without improving a decision. Begin with the audience and the question: what does this team need to understand, how often, and what action might follow from the result?

Document the current process and where it breaks down. The problem may be inconsistent definitions, slow preparation, an unclear source, or a report that does not match the way the team works. That diagnosis helps the project focus on the right part of the reporting chain.

Agree on what each metric means

Give important metrics a written definition. Include the population, calculation, unit, reporting period, exclusions, and owner. Two figures can both be calculated correctly and still answer different questions if those assumptions are not aligned.

Review examples with the people who use and maintain the report. Explain how filters, adjustments, and timing affect the result. Keep unresolved differences visible rather than embedding them in a calculation that only the developer understands.

• Name the business owner of each key metric.
• State the reporting period and relevant time boundaries.
• Document exclusions and the treatment of missing records.
• Agree on a review process for definition changes.

Shape the model around consistent detail

Microsoft’s star-schema guidance distinguishes fact tables from dimension tables and emphasizes a consistent grain for facts. That is a useful modeling reference when a report combines measurements with the descriptive information used to filter and group them.

For the project team, the practical question is what one row represents and how tables relate. Check whether joins duplicate a measure, whether history is handled consistently, and whether a filter changes the population in the intended way. Resolve those questions before treating a chart as an authoritative answer.

Technical references: Microsoft Learn — Star schema and semantic-model design (opens in a new tab)

Validate the numbers and the reading experience

Reconcile representative results with agreed source records and calculations. Test common filters, edge cases, and the periods the business reviews most often. Include the users who can explain whether an unexpected result is a data issue, a definition issue, or a real change in activity.

Then review how the report communicates. Labels, units, time periods, and comparisons should make the intended question easy to understand. Give users a way to find the definition and raise an issue when a number does not make sense.

Improve one recurring reporting decision

Choose a recurring report with a defined audience and an agreed business owner. Establish a small set of metrics, validate the supporting dataset, and review whether the result improves the team’s actual decision process.

DUB Consulting helps connect business questions with shared definitions, usable datasets, and decision-ready reporting. The work can include the integration and quality questions behind the dashboard so that the visible report rests on an explainable foundation.