Business intelligence architecture for growing companies

A useful business intelligence (BI) architecture gives people a dependable route from a business question to a decision. For a growing company, the first task is to identify where an important figure comes from, how it is calculated, when it updates and who can use it. Those responsibilities do not require a separate product for every step.

Turn objectives into a delivery sequence

Set the direction before selecting a solution: identify BI focus areas and objectives, then describe the outcomes that would show progress. Translate those outcomes into specific, achievable key results, and plan solutions around the data needs of the users who can contribute to them.

Bring the right people into solution planning. BI and analytics managers can oversee strategically important work. IT, BI teams and a Centre of Excellence can help design and deploy it. Subject matter experts, content owners and creators contribute business requirements and content knowledge.

Treat a solution as the smallest useful means of addressing a defined data need. It might be a pipeline, a lakehouse, a model or a report, rather than a commitment to build every architecture layer at once.

Trace one reporting flow

Start with a decision. A service manager, for example, might need to know whether unresolved work is rising before assigning staff. Identify the system that records each case, what counts as open or closed, the reporting cutoff, the calculation and the intended audience. The definitions must come from the business using the report.

If case status changes after a daily extract, readers need to know the report's update schedule. If teams disagree about closure rules, the measure needs an owner. If case notes are unnecessary for the decision, leave them out of a broadly available management view.

Give each responsibility a place

These are responsibilities, not necessarily six products. The test is whether someone can trace a reported figure to its source and explain its assumptions.

Share definitions where they need to agree

If several maintained reports need the same approved count of completed orders, a shared model can hold that measure while each report presents it for its own audience. A temporary investigation may need only a local dataset. Define a shared model's boundary by the questions it answers, its data grain, its owner and its users. Forcing every subject into one model can make it difficult to maintain.

A separate warehouse is also a workload decision. Large or complex transformations, several sources, or reporting that strains an operational system may justify one. A modest report from a stable source may not.

When to Use a Shared Model vs. Local Dataset

Let reporting grow around a supported core

As more teams need reports, a managed self-service approach can separate responsibility for the shared architecture from responsibility for departmental reporting. A centralised team of BI experts can maintain the architecture, while report creators in departments reuse approved shared models to build content for timely decisions.

This approach allows more people to create reports than models, without requiring every report creator to build and maintain a separate model. It depends on making reusable models suitable for their users, while keeping report development flexible at the edges.

Make freshness and quality visible

Set the update pattern from the decision's timing. A weekly review and a queue monitored during the day may need different schedules. Show the source cutoff and the last successful update so readers can recognise an incomplete period. In a Power BI Import model, source changes appear only after the model is refreshed; other connection modes have different behaviour.

Check the data that matters to the decision: required identifiers, missing fields, duplicate events and selected totals compared with the source for the same period. Assign someone to investigate failed checks and decide what readers should see while a problem is unresolved.

Data Freshness and Quality Indicators

Plan access and changes

Decide separately who may view a report, build another report from its model, change the model and export detail. A visual filter is not an access rule. Exclude unnecessary sensitive fields from a broadly available model and check the chosen platform's effective permissions.

When a shared measure, mapping or relationship changes, identify the dependent reports and check their figures and labels. Record the definition, effective date and owner. A dependency diagram helps locate affected work; it does not establish that the results remain correct.

Treat content as having a lifecycle from creation through eventual retirement. Planning its design and requirements early helps determine how it will be managed and delivered. Revisit that approach as content changes or is no longer needed.

Build one traceable slice

Choose a question with a decision maker and an accessible source. Define its measure and cutoff, then build the smallest reporting path that answers it. Compare a fixed period with an agreed source reference.

Ask the intended reader what action the result supports and whether its limits are clear. Extend the architecture after that path has an owner, a repeatable update and a way to handle changes.

Phase delivery through validation

Agree on requirements and the solution design with the project team, then prepare the tools and processes needed for deployment. Before building out the full solution, use a proof of concept to test assumptions about that design and expose issues early.

Create and validate content through iterative development cycles. Use the intended users and business experts to check whether the result addresses the agreed need, and refine it when validation shows that an assumption or requirement was wrong.

Assign someone to support and monitor the solution after deployment.