Data preparation
More than 25 Power Query transformations standardize types, handle missing or inconsistent values, reshape operational tables, create reusable keys, and prepare clean dimensions and facts for analysis.
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.
Dimensional model
Eight connected tables are organized as a star schema with controlled relationships, shared date logic, and reusable business definitions so every report page calculates from the same analytical foundation.
DAX & time intelligence
More than 30 measures calculate MRR, churn, customer health, revenue growth, prior-year comparison with SAMEPERIODLASTYEAR, adoption, CSAT, resolution time, and SLA compliance under the correct filter context.
Quality assurance
Measure outputs, totals, relationship behaviour, blank handling, and period comparisons are checked before presentation so attractive visuals do not hide inconsistent business logic.
Analysis & reporting
Five role-specific pages connect commercial, customer, product, billing, and support evidence while preserving drill-down paths from executive KPIs to operational drivers.
Business value
Each audience receives the few metrics that drive its decisions, including 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
Documents the power bi alerts authoring stage of Executive Performance Analytics and the evidence available to its user.