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.

Day 1Get 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