Beyond the Analytics: Why Mapping Use Cases Unlocks True BI Value

Insights
Written By Katy McIntyre

In many organisations, data analytics remains a reactive chore: a monthly deck, a spreadsheet sent around, a set of static visuals to review in meetings.

But modern analytics needs to be different. It needs to be timely, purposeful and rooted in well-defined business use cases.

At Flock, we’ve found that the strongest analytics initiatives begin with a simple question:

“What are we trying to solve?”

We start every project by mapping out:

  • Priority – Which use cases matter most right now?

  • Use Case + Objective – What specific decision or question are we answering?

  • Benefits – What value or insight will this unlock?

  • Data Sources – Where do the metrics live today?

That front-loaded thinking means the dashboards we build aren’t just polished, they’re actually useful, aligned with real business goals, and easier to adopt.

1. Priority: Focus Where It Counts

It’s tempting to build one dashboard for everything. But following Microsoft’s Power BI guidance, the best projects begin by focusing on specific scenarios and personas - from frontline operators to executive teams. Keeping scope tight ensures speed, clarity, and adoption.

2. Use Case + Objective: Frame Decisions Clearly

As an example, instead of “show sales performance,” we define the question more precisely:

“Which customer segments are underperforming, and why?”

This aligns with Microsoft’s focus on business requirements‑driven design for Power BI projects. It’s not window dressing, it’s decision support.

3. Benefits: Tie Metrics to Outcomes

If accurate, this insight can drive faster interventions, targeted campaigns and better results. Mapping benefits up‑front means we know when something is working and get buy‑in early.

4. Data Sources: Know Where to Connect

Powering a dashboard means knowing where the data lives - CRM, ERP, support logs, spreadsheets, or Azure Data Lake. Microsoft’s new Direct Lake capability helps teams query large data sources live, with fast performance and no duplication. Azure Data Explorer connectors in Power BI allow efficient handling of large datasets - if designed right.

5. Secure & Scale with Azure + Power BI

Once use cases are clear, we build them on a foundation that’s secure and scalable:

  • Microsoft published a Power BI Security Baseline on Azure (Feb 2025), covering network, identity, access control, data protection, and monitoring. Read more here.

  • A new Power BI security whitepaper (June 2025) walks through cloud-native, multilayered protection - from authentication to encryption to audit logging. Read more here.

Bringing It All Together In Practice

Here’s what this approach looks like end-to-end:

  • Align on use case priorities, stakeholders, outcomes, and data sources

  • Choose storage/connectivity → e.g., Azure Data Explorer, Databricks.

  • Implement RBAC, encryption, sensitivity labels per Microsoft guidance.

  • Roll out to core users → iterate on needs and trust.

  • Add Power BI learning pathways → promote ownership and exploration.

Why It Works

  • Purposeful design drives trust. Teams see the point early and adopt more readily.

  • Scenario focus speeds up delivery and keeps effort relevant.

  • Modern Azure + Power BI architecture scales securely - across roles and data volumes.

  • Governance-native approach means reporting is trusted from day one.

Great analytics aren’t just built, they’re designed, scoped, and connected. Start with clear use cases:
Priority → Use Case → Objective → Benefit → Data Source.

With that map, modern architecture, and Microsoft’s own best‑practice frameworks and security guidance, reporting becomes a driver of action, not a static deliverable.

If your current BI efforts feel like reports for the sake of reports, mapping your goals more deliberately could make all the difference.


References:

Katy McIntyre
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