Situation
Revenue, customer, product, billing, and support data lived in eight disconnected operational tables, leaving no shared, trustworthy KPI layer for different stakeholders to make decisions from.
Data Analytics
Executive Performance Analytics
A five-page Power BI decision system built from eight connected tables, combining revenue, customer health, product usage, billing, and support performance.
Why it matters
Turns disconnected operational data into a shared KPI and action layer.
My role
Data analyst, BI developer, and decision-support designer
- 01Profiled, cleaned, typed, joined, and transformed eight operational source tables through more than 25 reproducible Power Query steps.
- 02Designed a reusable star schema and more than 30 governed DAX measures with consistent filter and time-intelligence behaviour.
- 03Validated KPI totals and relationships, then designed decision-specific views for executive, finance, customer success, product, and support stakeholders.
Task
Build a five-page Power BI decision system on a governed data model, so executive, finance, customer-success, product, and support teams calculate from the same numbers instead of reconciling conflicting reports.
Action
- More than 25 Power Query transformations standardize types, handle missing or inconsistent values, and reshape the eight operational tables into clean dimensions and facts.
- The tables are organized into a star schema with controlled relationships and shared date logic, so every report page calculates from the same analytical foundation.
- More than 30 governed DAX measures calculate MRR, churn, customer health, revenue growth, adoption, CSAT, resolution time, and SLA compliance, using SAMEPERIODLASTYEAR time intelligence for correct filter-context behaviour.
- Measure outputs, totals, relationship behaviour, and period comparisons are validated before presentation, so polished visuals never hide inconsistent business logic.
Result
Five role-specific pages connect commercial, customer, product, billing, and support evidence with drill-down paths from executive KPIs to operational drivers, giving each audience the few metrics that actually drive its decisions: revenue leakage, at-risk customers, engagement, and support delivery.
Technical implementation
How the solution was built.
Each layer connects an implementation choice to the decision or workflow it supports.
06 layers| Layer | Implementation | Operational purpose |
|---|---|---|
| Source preparation | Eight operational tables processed through more than 25 Power Query transformations | Standardize types, keys, missing values and business-ready fields |
| Analytical model | Star schema with shared dimensions, controlled relationships and a reusable date table | Keep every report page on one consistent analytical foundation |
| Metric layer | More than 30 governed DAX measures for MRR, churn, health, adoption, CSAT and SLA | Create reusable KPI definitions that respond correctly to filter context |
| Time intelligence | Prior-period and year-over-year logic including SAMEPERIODLASTYEAR | Replace manually maintained comparisons with repeatable period analysis |
| Validation | Relationship, total, blank, filter and period-comparison checks | Verify business logic before presenting polished visuals |
| Decision views | Five pages tailored to executive, finance, customer, product and support questions | Move each stakeholder from headline KPI to the driver requiring action |
Product walkthrough
Screens connected to decisions.
executive overview
Presents leadership with the essential business-health indicators in a ten-second view.
revenue finance
Connects recurring revenue, growth, discounts, billing health, and year-over-year movement.
customer analytics
Surfaces retention, cohort behaviour, churn exposure, and customers requiring attention.
product usage health
Relates product adoption and engagement to account health and retention risk.
support sla
Tracks service delivery through SLA compliance, response performance, workload, and satisfaction.
power bi alerts authoring
Shows how threshold-based alerts are authored directly inside the Power BI report.