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Microsoft - Power Query

Transforming Data with Power BI

COURSE DESCRIPTION

After we’ve extracted data from a source, we often need to clean, or change, that data in preparation for loading it into Power BI. In this course, we’ll explore the options Power BI offers to unpivot, filter, sort, aggregate and perform other needed operations to make these preparations. We’ll employ a dataset containing issues that commonly present real-world challenges, and work through the steps we can take in Power Query to transform the data to a state that works best within Power BI. We’ll define calculations and get a glimpse of the M language that underlies transformational processes we construct.

A fully interactive experience, our online classroom offers a unique opportunity to learn from and work with a subject matter expert. Participants get practice performing the skills and can ask questions of the instructor in real time.

Class Length

One Day

CLASS MATERIALS

Students receive a comprehensive set of learning materials, including all course notes and class examples.

COST

$599

Class Outline
  • Introduction and overview of transforming data with Power BI
  • Preparation: create a new Power BI model
  • Introducing Query editor
    • Query editor environment
      • Launch Power Query
      • Navigate and understand options in the tabs
        • Home
        • Transform
        • Add column
        • View
  • Queries
    • Queries pane
    • Query settings pane
  • Data preview
    • Read-only view of source schema and data
    • Data filtering
    • Preview caching
    • Auto-discovery of relationships
  • Transforming data
    • General transformation types
      • Common basic transformations
        • Transforming data: scenario
        • Explore source data
        • Remove rows and columns
        • Un-pivot columns
        • Add custom columns
      • Loading data
        • Loading data: scenario
        • Load data
  •  Advanced features
    • Advanced features sampler
      • Transforming data: scenario
    • Combining data sets
      • Merge queries
      • Append queries
    • Use a function
      • Create a function based on internal functions
      • Generate date table as a new function
  • Summary and looking ahead