Model Online / On-Site
Duration
Modules 6 modules

Course Objective & Scope

Most wrong totals and convoluted formulas in Power BI reports stem from a weak data model. The programme clarifies dimensional modelling, star schemas, grain, relationship cardinality and filter direction, and the difference between calculated columns and measures.

Participants then write the most frequently used DAX patterns hands-on, including CALCULATE, filter context, time intelligence and share/percentage calculations. They transform a flat Excel dataset step by step into a star schema and build a measure library the team can reuse.

Who Should Attend?

  • Reporting analysts familiar with basic Power BI use
  • Specialists performing finance and sales analysis
  • Users moving from Excel Power Pivot to Power BI
  • Prerequisite: experience building reports in Power BI Desktop

Key Takeaways

  • Split flat datasets into fact and dimension tables
  • Create relationships with the right cardinality and filter direction
  • Choose correctly between calculated columns and measures
  • Write measures using CALCULATE and filter context
  • Produce YTD, MoM and YoY calculations with a date table

Curriculum

Dimensional Modelling and Star Schema
  • Fact and dimension tables, grain
  • Problems with snowflake and flat-table models
Relationships, Cardinality and Filter Direction
  • One-to-many and many-to-many relationships
  • Risks of bidirectional filtering and inactive relationships
Introduction to DAX: Columns and Measures
  • Row context and filter context
  • SUM, SUMX, DIVIDE and basic aggregation functions
CALCULATE and Filter Manipulation
  • ALL, REMOVEFILTERS and KEEPFILTERS
  • Share, ratio and target comparison measures
Date Tables and Time Intelligence
  • Creating and marking a date table
  • YTD, prior period and moving average calculations
Case: From Excel to Star Schema
  • Turning a flat dataset into a model
  • Measure library and naming standards

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