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COURSE TOPIC

Power BI Dashboards: Power Query, Data Models and DAX

Prepare data with Power Query, model relationships, write DAX measures, and design interactive dashboards.

Part of course Data Analyst Course
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Difficulty Level
Intermediate
Estimated Learning Time
4-5 hours
OVERVIEW

About Power BI Dashboards: Power Query, Data Models and DAX

Power BI helps analysts create reports that explore business measures and trends. Useful dashboards rely on prepared data, sound relationships, clear measure definitions, and visuals that answer questions.

LEARNING OUTCOMES

What You Will Learn

  • Transform and validate data using Power Query.
  • Create relationships between fact and dimension tables.
  • Write DAX measures for KPIs and comparisons.
  • Choose visuals and test report filters.
TOPIC GUIDE

Learn Power BI Dashboards: Power Query, Data Models and DAX

Prepare data with Power Query

Power Query connects to sources and records transformations. Rename fields, set types, remove unwanted rows, standardize values, and combine queries. Review steps and refresh to confirm they work with updated data.

Build a dependable model

Relationships organize tables so filters behave predictably. Separate descriptive information such as products and dates from transaction records where appropriate. Check relationship keys and test slicer behavior.

Write DAX measures

DAX measures calculate results in the current filter context. Define totals, ratios, and comparisons that respond to selections. Use clear names and validate results against known totals or a manual check.

Design a readable dashboard

Choose visuals to match the question: cards for KPIs, lines for trends, and bars for comparisons. Use clear labels, restrained colors, and useful slicers. Remove visuals that do not support the analysis.

Practice

Prepare sales data with date, product, region, quantity, and unit price. Create a date table and relationships, then measures for revenue, order count, and average order value. Build KPI cards, a trend, and category comparison; add a region slicer and verify interactions.

PRACTICAL EXAMPLE

Example / Code

Example 
Total Revenue = SUMX(Sales, Sales[Quantity] * Sales[Unit Price])
Order Count = DISTINCTCOUNT(Sales[Order ID])
Average Order Value = DIVIDE([Total Revenue], [Order Count])
TRY IT YOURSELF

Practice Task

Apply what you learned with a practical activity.

Build a report with Power Query cleaning, a date table, revenue and order measures, KPI cards, a trend, category comparison, and a region slicer. Independently validate one KPI.

TOOLKIT

Tools & Technologies

  • Power BI Desktop
  • Power Query
  • Data modeling
  • DAX
  • Visualizations
CONTINUE LEARNING

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