Modeling Data in Power BI
Learn how to work with data that comes from different sources and is structured in different ways by using Power BI transformations to combine, reshape, cleanse, and enhance that data to create a model that supports reporting and analytics.
What you'll learn
Data in its raw form is rarely useful for reporting and analysis. In this course, Modeling Data in Power BI, you'll learn how to use Power BI to transform raw data into meaningful insights. First, you'll learn how to gather data and apply transformations to easily blend multiple sources together, reduce the data to its most useful elements, and prepare the data for exploration. Next, you'll discover how to configure the model to support Power BI features for insightful visualizations, geospatial analysis, and natural language queries. Finally, you'll explore the basics of DAX, Power BI's expression language, to add calculations to your model. When you're finished with this course, you'll have the skills and knowledge of Power BI data modeling that you can use to build your own models that support a variety of analytical requirements and take full advantage of Power BI's capabilities.
Table of contents
- Overview 2m
- Supported Data Sources 5m
- Exploring Power BI Data Sources 3m
- Model Requirements 2m
- Movies Model Data 3m
- Loading Data: Movies_metadata.csv 2m
- Loading Data: Names_ak.tsv and Names_lz.tsv 7m
- Loading Data: Principals.tsv 2m
- Loading Data: Awards HTML Table 2m
- Applying Query Changes 2m
- Reviewing Query Errors 2m
- Counting Loaded Rows 4m
- Power Query Editor vs. Power BI Desktop 5m
- Assessing the State of the Model 1m
- Summary 2m
- Overview 2m
- Common Transformations 2m
- Renaming Queries 2m
- Eliminating Columns in a Query 2m
- Filtering Rows in a Query 3m
- Merging Queries to Filter Rows 5m
- Renaming Columns 4m
- Changing Data Types 3m
- Replacing Values 3m
- Splitting Columns 7m
- Understanding Custom Columns 3m
- Adding Custom Columns 5m
- Other Transformations 1m
- Duplicating vs. Referencing a Query 3m
- Using Unpivot 2m
- Introducing the Star Schema 2m
- Dimensions 2m
- Facts 2m
- Creating Movie Revenues 4m
- Creating Movie Values Fact and Movies Dimension 6m
- Assessing the State of the Model 2m
- Summary 1m
- Overview 2m
- Understanding Relationships 4m
- Checking for Relationship Problems in the Model 7m
- Introducing the Model Diagram 4m
- Introducing the Relationship Editor 3m
- Creating Relationships 4m
- Fixing Data Quality Issues 4m
- Adjusting Relationship Cardinality 3m
- Understanding Cross Filter Direction 3m
- Working with an Ad Hoc Hierarchy 3m
- Adding a Permanent Hierarchy to the Model 3m
- Summary 3m
- Overview 1m
- Configuring Model Properties 3m
- Renaming, Hiding, and Describing Objects 5m
- Formatting Numeric and Date Values 4m
- Configuring Default Summarization 3m
- Aggregations 2m
- Using Data Categories 2m
- Assigning a Field to the Web URL Data Category 2m
- Assigning a Field to the Image URL Data Category 2m
- Understanding Q&A 2m
- Using Q&A 3m
- Adding a Synonym to the Model 3m
- Introducing the Linguistic Schema 4m
- Editing the Linguistic Schema 2m
- Summary 1m
- Overview 3m
- Introducing DAX 2m
- Defining New Columns: Concatenating Columns 6m
- Defining New Columns: Translating a Value 7m
- Using Variables in a DAX Expression 2m
- Defining New Columns: Performing a Lookup to a Related Table 5m
- Creating Measures 3m
- Adding Measures to the Model 3m
- Using DAX Parameters: Creating Query Parameters 6m
- Using DAX Parameters: Using Query Parameters 3m
- Using DAX Parameters: Working with What if Parameters 4m
- Summary 3m
- Overview 2m
- Creating a Calculated Date Table 4m
- Activating a Relationship with DAX 3m
- Using DAX Functions for Date and Time Operations 3m
- Creating Calculated Columns for a Date Table 5m
- Adding a Custom Date Hierarchy 2m
- Applying Time Intelligence 1m
- Using the TOTALYTD() Function 3m
- Using the SAMEPERIODLASTYEAR() Function 3m
- Using the OPENINGBALANCEMONTH() Function 2m
- Summary 2m
- Overview 2m
- Introducing Row Context 2m
- Exploring Row Context 4m
- Using Iterator Functions 7m
- Understanding Filter Context 2m
- Using the CALCULATE Function to Apply a Filter 3m
- Calculating a Percent of Total 5m
- Using the FILTER() Function 2m
- Working with Parent-child Functions 1m
- Using the PATH() and PATHITEM() Functions 4m
- Using the PATHLENGTH() and ISFILTERED() Functions 3m
- Summary 2m
About the author
Stacia Misner Varga is an instructor, author, and principal consultant of Data Inspirations. Her career spans more than 30 years, with a focus on improving business practices through technology. Since 2000, she has provided consulting and education services for Microsoft’s data platform and authored or co-authored many books covering this topic. In addition, Stacia has been a frequent speaker over the years at technology conferences worldwide.