Power BI for Data Stewards
This training is designed for data wranglers, developers or data transformers, who want to transform raw data coming from one or more data sources and make that data ready for further analytics.
The emphasis on this course is how to turn low quality data into something that will help you to deliver the business value and the business insights you need to make the right decisions.
Koulutusmuoto
Remote
Kesto
3 päivää
Hinta
25900 kr
Target Audience
This is a next level course for persons such as Data Stewards, BI developers, ETL developers, and end users who want get more, deeper understanding of Power BI.
During the course you'll learn
- Get Data Power Query
- Data Types and Data Structures
- Combining Queries with Merge & Append
- Better Power Query Editor Experience
- Reducing Number of Rows
- Column Operations & Table Transformations
- Text Transformations & Numeric Transformations
- Structured Column Transformations & Add Column Transformations
- Error Handling
- Date and Time Transformations
- Dynamic Power Query with Functions and Parameters
- Introducing Power Query Formula Language
- M Working with Data Structures in M Advanced M Scripting
- Performance Tips and Tricks for Power Query Use Cases
Prerequisites
You should have the following knowledge before taking this course:
- how to get connected to your data and pull it in
- how to build out a basic data model
- how to build some basic visuals
- some basic DAX knowledge
Course content of Power BI for Data Stewards
Day 1
Get Data
- Introduction to Power Query
- Query Editor
- Get Data from Web
- Basic Transformations
- Get Data from Excel
- Use First Row As Headers / Use Headers as First Row
- Get Data from SQL Server
Data Types and Data Structures
- Base data structures in Power Query
- Get Data from JSON
- Transforming Table, Record, and List
- Data Types in Power Query
- Query Operations
- Enable Load; Performance Boost
- Query Operations; Duplicate, and Reference
Combine Queries
- Dimensional Modelling; Designing the data model
- Append, creating a single big query of the same structure
- Merge; Joining queries when the structure is different
- Join types in Merge
- Tips to consider after Merge or Append
Better Power Query Editor Experience
- Groups; Folders in Query Editor
- Steps Operations
- Splitting query steps
- Moving steps up or down
- Add as new query / Drill Down
- Be Careful of Actions; Undo!
Reducing Number of Rows
- Filtering
- Row Operations; Removing rows
- Row Operations; Keeping rows
- Remove/Keep Errors
- Remove/Keep Duplicates
- Using Remove/Keep combination for troubleshooting report
- Filtering based on Individual values
- The dilemma of the basic filtering
- Advanced Filtering
- Sorting
Column & Table Operations
- Scripting and Group by; First and Last item in each group
- Transpose; rows to columns and reverse
- Pivot; changing the name-value structure to columns
- Unpivot; changing the budget column structure to rows
Text Transformations
- Split Column by Delimiter
- Split Column by number of Characters
- Split into rows instead of columns
- Merge (Concatenate)
- Format
- The difference between Clean and Trim
- Parse (XML or JSON)
- Extract part of the text
Numeric Transformations
- Standard transformations
- Divide, Integer-divide, Multiply, Add etc.
- Scientific transformations; logarithm, power square, etc.
- Statistics transformations;
- Rounding
- Information functions; Is Even, Is Odd, and Sign.
- Dealing with faults in Numeric calculations
Structured Column & Add Column Transformations
- What is a Structured Column?
- Expand
- Aggregate
- Expand and Aggregate: Performance Consideration
- Add Column vs. Transform?
- Add Column with a Transformation
- Index Column: Row Number
- Conditional Column
- Add Column by Example; When you don’t know which transformation to use
- Add Custom Column: Generic
Day 2
Error Handling
- Keep/Remove Errors; Troubleshooting report
- Count Rows
- Reference/Duplicate
- Replace Errors
- Data Type considerations
Date and Time Transformations
- Date Transformations (Year, Month, Quarter, Week, etc.)
- Extending Fiscal Date Column
- Time Transformations (Hour, Minute, Second, etc.)
- Adding Time/Date banding
- Duration Transformation and Data Type
- Age Calculation
- Local Date or Time
- Time zone consideration for Power BI
Functions and Parameters; Dynamic Power Query
- Defining Parameters
- Using Parameters in an existing query
- Advanced GUI for parameters
- Creating Function from a query
- Invoking the sample function
- Add Column Transform: Invoke Custom Function
- When the advanced GUI does not exist
Power Query Formula Language: M
- What is M? and the importance of learning M
- M Syntax
- Variable Names
- Special Characters
- Escape Character
- Step by Step Coding
- Literals
- Function Call
- Comments
- A real-world example
Working with Data Structures in M
- List
- Record
- Table
- Function
- Navigating through List and List functions
- Navigating through Record and Record functions
- Navigating through Table and table functions
- Concatenating lists and record
Advanced M Scripting
- #Shared Keyword; function library of Power Query
- Parameters in the code
- Custom Functions through scripting
- Generators in Power Query: Implementing Loop Structure
- EACH: singleton function
- Sample Custom Function: Day Number of Year Custom Function
Performance Tips and Tricks for Power Query
- Enable Load; Simple, but Efficient
- Reducing Number of Columns
- Query Folding
- Grouping and Aggregation; Performance Consideration
- Merge; Before and After, things to Consider Use Cases
- Date Dimension with Power Query; building the base table
- Adding Fiscal columns to the Date dimension
- Getting public holidays live and merging to the date dimension
- Looping through files in a folder with Power Query
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