Modeling Data in Power BI
Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.
Modeling Data in Power BI
This course is part of Microsoft Power BI and Power Platform for Productivity Specialization
Instructor: Microsoft
2,677 already enrolled
Included with
Learn more
Ask Coursera
14 reviews
Recommended experience
14 reviews
Recommended experience
What you'll learn
How to form a model using a Star Schema.
How to write calculations DAX to create elements and analysis in Power BI.
How to optimize performance in a Power BI model.
Skills you'll gain
Tools you'll learn
Details to know
24 assignments
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this course
In this course, you'll learn how to use Power BI to create and maintain relationships in a data model and form a model using multiple Schemas. You'll explore the basics of DAX, Power BI's expression language, and add calculations to your model to create elements and analysis in Power BI. You'll discover how to configure the model to support Power BI features for insightful visualizations, analysis, and optimization.
After completing this course you'll be able to: β Create and maintain relationships in a data model. β Form a model using a Star Schema β Write calculations DAX to create elements and analysis in Power BI β Create calculated columns and measures in a model β Perform useful time intelligence calculations in DAX β Optimize performance in a Power BI model
This module introduces data modeling and the schemas used to create them.
What's included
13 videos20 readings6 assignments2 discussion prompts
13 videosβ’Total 68 minutes
- Course introductionβ’4 minutes
- Introduction to data modelsβ’5 minutes
- Introduction to schemasβ’6 minutes
- Setting up a Flat schema in Power BIβ’5 minutes
- Understanding fact and dimension tablesβ’4 minutes
- Introduction to cardinalityβ’5 minutes
- Introduction to cross-filter directionβ’5 minutes
- Defining data granularityβ’6 minutes
- Setting up a Star schema in Power BIβ’6 minutes
- Setting up a Snowflake schemaβ’6 minutes
- Why it is important to use Snowflake schemaβ’4 minutes
- Resolving challenges in data modelsβ’5 minutes
- Module summary: Concepts for data modelingβ’6 minutes
20 readingsβ’Total 225 minutes
- Course syllabusβ’10 minutes
- How to be successful in this courseβ’10 minutes
- How to open an image in a new tabβ’10 minutes
- Setting up your Power BI environmentβ’10 minutes
- Additional resources: Concepts for data modelingβ’5 minutes
- Model view in Power BIβ’10 minutes
- Schemas cheatsheetβ’10 minutes
- Table and column properties cheatsheetβ’10 minutes
- Exercise: Configuring a Flat schemaβ’30 minutes
- Exemplar: Configuring a Flat schemaβ’10 minutes
- Activity: Configure a Flat schema with multiple sourcesβ’10 minutes
- Additional resources: Introduction to data modelsβ’10 minutes
- Normalization and denormalizationβ’10 minutes
- Managing model relationshipsβ’10 minutes
- Model relationships cheatsheetβ’10 minutes
- Additional resources: Introduction to cardinality and cross-filter directionβ’5 minutes
- Exercise: Configuring a Star schemaβ’30 minutes
- Exemplar: Configuring a Star schemaβ’10 minutes
- Activity: Changing your Star schema into a Snowflake schemaβ’10 minutes
- Additional resources: Working with advanced data modelsβ’5 minutes
6 assignmentsβ’Total 95 minutes
- Module quiz: Concepts for data modelingβ’30 minutes
- Self-review: Configuring a Flat schemaβ’10 minutes
- Knowledge check: Introduction to data modelsβ’15 minutes
- Knowledge check: Introduction to cardinality and cross-filter directionβ’15 minutes
- Self-review: Configuring a Star schemaβ’10 minutes
- Knowledge check: Working with advanced data modelsβ’15 minutes
2 discussion promptsβ’Total 20 minutes
- Discussion prompt: What do you hope to learn?β’10 minutes
- Why is data modeling important in the data analysis process?β’10 minutes
This module introduces the learner to the DAX (Data Analysis Expressions) language. The module explores the syntax of DAX using multiple business use cases. The module also integrates DAX with previous lessons on database tables and their use and introduces the concept of time intelligence.
What's included
23 videos20 readings10 assignments1 discussion prompt
23 videosβ’Total 113 minutes
- Introduction to Data Analysis Expressions (DAX)β’6 minutes
- Row context and filter contextβ’6 minutes
- Formulas and functions in DAXβ’5 minutes
- Introduction to calculated tablesβ’5 minutes
- Creating calculated columnsβ’5 minutes
- Introduction to measuresβ’5 minutes
- Types of measuresβ’5 minutes
- Basic statistical functionsβ’5 minutes
- Context and DAX measuresβ’4 minutes
- Creating quick measuresβ’6 minutes
- Creating custom measures with DAXβ’4 minutes
- Introduction to the CROSSFILTER functionβ’5 minutes
- Using CALCULATE with filtersβ’5 minutes
- Introduction to role-playing dimensionsβ’6 minutes
- Introduction to the USERELATIONSHIP functionβ’5 minutes
- Configuring role-playing dimensionsβ’3 minutes
- The importance of time intelligenceβ’5 minutes
- Using DAX for summarization over timeβ’6 minutes
- Using DAX for comparison over timeβ’5 minutes
- Setting up a common date tableβ’5 minutes
- Setting up a common date table with M and Power Queryβ’4 minutes
- Time intelligence in businessβ’3 minutes
- Module summary: Using DAX in Power BIβ’7 minutes
20 readingsβ’Total 255 minutes
- DAX cheatsheetβ’10 minutes
- Cloning and calculating tablesβ’10 minutes
- Exercise: Adding a calculated table and columnβ’30 minutes
- Exemplar: Adding a calculated table and columnβ’10 minutes
- Additional resources: Introduction to DAXβ’5 minutes
- Statistical functions cheatsheetβ’10 minutes
- Additional resources: Introduction to measuresβ’5 minutes
- Exercise: Adding a measureβ’30 minutes
- Exemplar: Adding a measureβ’10 minutes
- Filter functions in CALCULATEβ’10 minutes
- Activity: Using the CALCULATE functionβ’10 minutes
- Additional resources: Working with measuresβ’5 minutes
- Exercise: Adding a role-playing dimensionβ’30 minutes
- Exemplar: Adding a role-playing dimensionβ’10 minutes
- Additional resources: DAX and table relationshipsβ’5 minutes
- Additional time intelligence functionsβ’10 minutes
- Exercise: Using time intelligence to compare to previous yearβ’30 minutes
- Exemplar: Using time intelligence to compare to previous yearβ’10 minutes
- Activity: Set up a common date tableβ’10 minutes
- Additional resources: Time intelligence and calculations in DAXβ’5 minutes
10 assignmentsβ’Total 145 minutes
- Module quiz: Using DAX in Power BIβ’30 minutes
- Self-review: Adding a calculated table and columnβ’10 minutes
- Knowledge check: Using Data Analysis Expressions (DAX) in Power BIβ’15 minutes
- Knowledge check: Introduction to measuresβ’15 minutes
- Self-review: Adding a measureβ’10 minutes
- Knowledge check: Working with measuresβ’15 minutes
- Self-review: Adding a role-playing dimensionβ’10 minutes
- Knowledge check: DAX and table relationshipsβ’15 minutes
- Self-review: Using time intelligence to compare to previous yearβ’10 minutes
- Knowledge check: Time intelligence calculations in DAXβ’15 minutes
1 discussion promptβ’Total 10 minutes
- Which DAX features did you find most useful?β’10 minutes
This module explores the optimization process and examines the tools and methods to achieve this in Power BI, including using performance analyzer and DirectQuery features. This module also dives deeper into DAX and its use in the real world.
What's included
10 videos12 readings6 assignments1 discussion prompt
10 videosβ’Total 59 minutes
- What is optimization and why is it necessary?β’7 minutes
- Optimization by exampleβ’7 minutes
- Resolving performance issues in the data modelβ’5 minutes
- Identifying and reducing cardinality levelsβ’6 minutes
- Behavior and limitations of DirectQuery connectionsβ’7 minutes
- Optimizing DirectQuery performance with query reductionsβ’4 minutes
- Optimizing DirectQuery performance with table storageβ’6 minutes
- What are aggregations and why use them?β’6 minutes
- Creating an aggregationβ’6 minutes
- Module summary: Optimize a model for performance in Power BIβ’8 minutes
12 readingsβ’Total 145 minutes
- Exercise: Improving data model performanceβ’30 minutes
- Exemplar: Improving data model performanceβ’10 minutes
- Optimizing columns and metadataβ’10 minutes
- Optimizing the Auto date/time featureβ’10 minutes
- Activity: Optimizing the columns and Auto date/timeβ’10 minutes
- Additional resources: Optimize performance in a Power BI modelβ’5 minutes
- Walk-through: Optimizing a DirectQuery modelβ’10 minutes
- Additional resources: Optimize DirectQuery modelsβ’5 minutes
- Exercise: Adding an aggregationβ’30 minutes
- Exemplar: Adding an aggregationβ’10 minutes
- How to manage aggregations step-by-step β’10 minutes
- Additional resources: Create and manage aggregationsβ’5 minutes
6 assignmentsβ’Total 95 minutes
- Module quiz: Optimize a model for performance in Power BIβ’30 minutes
- Self-Review: Improving data model performanceβ’10 minutes
- Knowledge check: Optimize a model for performance in Power BIβ’15 minutes
- Knowledge check: Optimize DirectQuery modelsβ’15 minutes
- Self-review: Adding an aggregationβ’10 minutes
- Knowledge check: Create and manage aggregationsβ’15 minutes
1 discussion promptβ’Total 10 minutes
- How would performance and optimization impact different stakeholders?β’10 minutes
In this module, you will be assessed on the key skills covered in the course. This module summarizes the course and reflects on the primary learning objectives. The module also contains the project for the course, which encapsulates the learning into a practical whole.
What's included
2 videos4 readings2 assignments1 discussion prompt
2 videosβ’Total 6 minutes
- Course recap: Modeling data in Power BIβ’3 minutes
- Congratulations!β’3 minutes
4 readingsβ’Total 60 minutes
- About the final project and assessment: Modeling data in Power BIβ’10 minutes
- Exercise: Building and optimizing a data modelβ’30 minutes
- Exemplar: Building and optimizing a data modelβ’10 minutes
- Next stepsβ’10 minutes
2 assignmentsβ’Total 105 minutes
- Self-review: Building and optimizing a data modelβ’15 minutes
- Course quiz: Modeling data in Power BIβ’90 minutes
1 discussion promptβ’Total 10 minutes
- Reflect on learningβ’10 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
Offered by
Explore more from Data Analysis
- Status: Free Trial
Course
- Status: PreviewS
Simplilearn
Course
- Status: Free TrialM
Microsoft
Course
Guided Project
Why people choose Coursera for their career
Frequently asked questions
This program is for you:
β If you want to switch or start a career in the field of data analytics.
β If you are interested in the field of data analytics, just beginning to work with business intelligence and data analysis solutions and services, or new to Microsoft Power BI.
You donβt need any background knowledge to take this Professional Certificate. Whether youβre just starting out or a professional in a relevant field, this program can be the right fit for you.
It typically takes 5 months to complete the 8 courses. But some learners may go through the content faster.
More questions
Financial aid available,
