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LinkedIn Learning

Power BI Data Methods

via LinkedIn Learning


Get a comprehensive overview of the data end of Power BI—also known as Power Query—and learn how to use it to automate the data querying process and restructuring of data sets.


  • The Power BI ecosystem
  • What is Power BI?
  • Understanding ETL (extract, transform, and load)
  • Focus on Power Query
  • Course considerations
1. Extracting Data: Files
  • Connecting to CSV or text files
  • Manually entering data
  • Connecting to an Excel file
  • Connecting to a PDF file
  • Connecting to folders
2. Extracting Data: Databases
  • Connecting to databases
  • Comparing data connection modes
  • Query folding and native queries
3. Extracting Data: Web and Other Options
  • Connecting to web tables
  • Querying API data
  • Querying REST API connections
  • Configuring OData feeds
  • Installing Python
  • Running Python scripts
4. Transforming Data: Cleaning
  • Leveraging metadata
  • Leveraging data types
  • Making initial field transformations
  • Splitting fields
  • Merging fields
  • Cleaning text fields
  • Transforming numerical fields
  • Removing or replacing values
  • Filtering and removing duplicates
  • Accessing native query in cleaning
5. Transforming Data: Integration
  • Introducing table objects
  • Introducing list and record objects
  • Working with binary objects
  • Grouping data
  • Pivoting data
  • Transposing data
  • Unpivoting data
  • Accessing native query in integration
6. Transforming Data: Enrichment
  • Leveraging text formulas
  • Conditional formulas
  • Filling up or down columns
  • Leveraging date formulas
  • Combining binary files with formulas
  • Accessing native query in enrichment
7. Leveraging M Language: Logic and Syntax
  • Working with Query Editor steps
  • Breaking down syntax
  • Renaming steps in M
  • Consolidating M steps
  • Adding data types as custom M code
  • Connecting to zipped binary data
8. Leveraging M Language: Objects
  • Utilizing parameters
  • Creating list objects
  • Referencing a list as a column in a table
  • Leveraging record objects
  • Leveraging list functions
  • Creating date tables
  • Looping with lists
  • Combining list objects
9. Leveraging M language: Custom Functions
  • Setting up custom functions
  • Converting queries into functions
  • Configuring custom filtering
10. Loading Data
  • Configuring loading options
  • Fixing errors
  • Refreshing data
  • Joining sets of data
  • Composite models
  • Next steps

Taught by

Helen Wall


4.5 rating at LinkedIn Learning based on 441 ratings

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