From raw business data to an executive dashboard. Learn Power Query, modelling, DAX, visualisation and commercial analysis through practical exercises and a 624-row fictional business dataset.
This is not just chart-building. Learners are asked to explain what changed, why it matters, where the problem sits and what management should do next.
Final output:Executive Power BI dashboard + written management recommendations.
The modules progress from beginner foundations into management-level analysis and an independent final challenge.
Desktop vs Service, interface, report/data/model views and the end-to-end analytics workflow.
Rows, dimensions, measures, granularity, KPIs, targets and asking useful management questions.
Excel, CSV and folder-based imports; data-source settings and refresh concepts.
Applied steps, data types, rename/remove, filters and reproducible transformation.
Nulls, errors, duplicates, split/merge, replace values and quality checks.
Append weekly files, merge lookup tables and create repeatable folder workflows.
Fact vs dimension tables, star schema, cardinality and filter direction.
Calendar tables, date relationships, month/quarter/year fields and sorting.
Measures, calculated columns, filter context and core aggregation functions.
DIVIDE, CALCULATE, variables, conditional logic and reusable KPI measures.
YTD, prior year, YoY growth, rolling trends and comparable-period thinking.
Actual vs budget, variance £/%, labour %, productivity, quality and service metrics.
Cards, trends, bars, matrices, conditional formatting and choosing the right visual.
Slicers, drill-through, tooltips, bookmarks and report navigation.
Move from headline KPI to site, region, week and driver-level investigation.
Information hierarchy, management storytelling and decision-focused page design.
Workspace concepts, refresh, sharing, permissions, privacy and responsible data handling.
Clean an unseen dataset, model it, write DAX, build a dashboard and present recommendations.
The downloadable workbook contains 12 sites across 52 weeks. Figures are deliberately varied so learners can uncover hidden operational issues.
The board says revenue is growing, but performance is inconsistent. Build the report and determine which sites need management attention and why.
Total Revenue • Budget • Variance £ • Variance % • Revenue LY • YoY Growth %
Labour Cost • Labour % • Revenue per Labour Hour • Transactions
Error Rate • Average SLA • Quality Score • Customer Score
Learners clean and model data, create measures, build a one-page executive dashboard, identify hidden performance problems and present a concise action plan.