Overview
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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.
Syllabus
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Introduction
- The Power BI ecosystem
- What is Power BI?
- Understanding ETL (extract, transform, and load)
- Focus on Power Query
- Course considerations
- Connecting to CSV or text files
- Manually entering data
- Connecting to an Excel file
- Connecting to a PDF file
- Connecting to folders
- Connecting to databases
- Comparing data connection modes
- Query folding and native queries
- Connecting to web tables
- Querying API data
- Querying REST API connections
- Configuring OData feeds
- Installing Python
- Running Python scripts
- 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
- 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
- Leveraging text formulas
- Conditional formulas
- Filling up or down columns
- Leveraging date formulas
- Combining binary files with formulas
- Accessing native query in enrichment
- 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
- 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
- Setting up custom functions
- Converting queries into functions
- Configuring custom filtering
- Configuring loading options
- Fixing errors
- Refreshing data
- Joining sets of data
- Composite models
- Next steps
