Data Modeling in Power BI

This course is part of Microsoft Power BI Data Analyst Professional Certificate

Instructor: Microsoft

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.

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Assessments

24 assignments

Taught in English

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This course is part of the Microsoft Power BI Data Analyst Professional Certificate

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There are 4 modules in this course

This course forms part of the Microsoft Power BI Analyst Professional Certificate. This Professional Certificate consists of a series of courses that offers a good starting point for a career in data analysis using Microsoft Power BI.

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: ● Create and maintain relationships in a data model. ● Form a model using a Star Schema ● Write calculations DAX to create elements and analysis in Power BI ● Create calculated columns and measures in a model ● Perform useful time intelligence calculations in DAX ● Optimize performance in a Power BI model This is also a great way to prepare for the Microsoft PL-300 exam. By passing the PL-300 exam, you’ll earn the Microsoft Power BI Data Analyst certification.

This module introduces data modeling and the schemas used to create them.

What's included

13 videos23 readings6 assignments2 discussion prompts

13 videosTotal 67 minutes

Course introduction4 minutesPreview module
Introduction to data models4 minutes
Introduction to schemas6 minutes
Setting up a Flat schema in Power BI4 minutes
Understanding fact and dimension tables3 minutes
Introduction to cardinality5 minutes
Introduction to cross-filter direction4 minutes
Defining data granularity5 minutes
Setting up a Star schema in Power BI5 minutes
Setting up a Snowflake schema6 minutes
Why it is important to use Snowflake schema4 minutes
Resolving challenges in data models5 minutes
Module summary: Concepts for data modeling6 minutes

23 readingsTotal 250 minutes

Course syllabus10 minutes
How to be successful in this course10 minutes
How to open an image in a new tab10 minutes
Setting up your Power BI environment10 minutes
New name for Power BI datasets10 minutes
How to locate your downloaded files10 minutes
Additional resources: Concepts for data modeling5 minutes
Model view in Power BI10 minutes
Schemas cheatsheet10 minutes
Table and column properties cheatsheet10 minutes
Exercise: Configuring a Flat schema30 minutes
Exemplar: Configuring a Flat schema10 minutes
Activity: Configure a Flat schema with multiple sources10 minutes
Additional resources: Introduction to data models5 minutes
Normalization and denormalization10 minutes
Managing model relationships10 minutes
Model relationships cheatsheet10 minutes
Additional resources: Introduction to cardinality and cross-filter direction5 minutes
Exercise: Configuring a Star schema30 minutes
Exemplar: Configuring a Star schema10 minutes
Activity: Changing your Star schema into a Snowflake schema10 minutes
Data View in Power BI10 minutes
Additional resources: Working with advanced data models5 minutes

6 assignmentsTotal 95 minutes

Module quiz: Concepts for data modeling30 minutes
Self-review: Configuring a Flat schema10 minutes
Knowledge check: Introduction to data models15 minutes
Knowledge check: Introduction to cardinality and cross-filter direction15 minutes
Self-review: Configuring a Star schema10 minutes
Knowledge check: Working with advanced data models15 minutes

2 discussion promptsTotal 20 minutes

Discussion prompt: What do you hope to learn?10 minutes
Why is data modeling important in the data analysis process?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 videos21 readings10 assignments1 discussion prompt

23 videosTotal 113 minutes

Introduction to Data Analysis Expressions (DAX)5 minutesPreview module
Formulas and functions in DAX5 minutes
Row context and filter context5 minutes
Introduction to calculated tables4 minutes
Creating calculated columns4 minutes
Introduction to measures4 minutes
Types of measures4 minutes
Basic statistical functions5 minutes
DAX measures and context in business4 minutes
Creating quick measures5 minutes
Creating custom measures with DAX4 minutes
Introduction to the CROSSFILTER function4 minutes
Using CALCULATE with filters5 minutes
Introduction to role-playing dimensions5 minutes
Introduction to the USERELATIONSHIP function4 minutes
Configuring role-playing dimensions2 minutes
The importance of time intelligence4 minutes
Using DAX for summarization over time6 minutes
Using DAX for comparison over time5 minutes
Setting up a common date table using DAX5 minutes
Setting up a common date table with M and Power Query3 minutes
Time intelligence in business2 minutes
Module summary: Using DAX in Power BI6 minutes

21 readingsTotal 265 minutes

DAX cheatsheet10 minutes
Cloning and calculating tables10 minutes
DAX table functions10 minutes
Exercise: Adding a calculated table and column30 minutes
Exemplar: Adding a calculated table and column10 minutes
Additional resources: Introduction to DAX5 minutes
Statistical functions cheatsheet10 minutes
Additional resources: Introduction to measures5 minutes
Exercise: Adding a measure30 minutes
Exemplar: Adding a measure10 minutes
Filter functions in CALCULATE10 minutes
Activity: Using the CALCULATE function10 minutes
Additional resources: Working with measures5 minutes
Exercise: Adding a role-playing dimension30 minutes
Exemplar: Adding a role-playing dimension10 minutes
Additional resources: DAX and table relationships5 minutes
Additional time intelligence functions10 minutes
Exercise: Using time intelligence to compare to previous year30 minutes
Exemplar: Using time intelligence to compare to previous year10 minutes
Activity: Set up a common date table10 minutes
Additional resources: Time intelligence and calculations in DAX5 minutes

10 assignmentsTotal 145 minutes

Module quiz: Using DAX in Power BI30 minutes
Self-review: Adding a calculated table and column10 minutes
Knowledge check: Using Data Analysis Expressions (DAX) in Power BI15 minutes
Knowledge check: Introduction to measures15 minutes
Self-review: Adding a measure10 minutes
Knowledge check: Working with measures15 minutes
Self-review: Adding a role-playing dimension10 minutes
Knowledge check: DAX and table relationships15 minutes
Self-review: Using time intelligence to compare to previous year10 minutes
Knowledge check: Time intelligence calculations in DAX15 minutes

1 discussion promptTotal 10 minutes

Which DAX features did you find most useful?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 videosTotal 59 minutes

What is optimization and why is it necessary?6 minutesPreview module
Optimization by example6 minutes
Identifying and reducing cardinality levels5 minutes
Resolving performance issues in the data model4 minutes
Behavior and limitations of DirectQuery connections6 minutes
Optimizing DirectQuery performance with query reductions3 minutes
Optimizing DirectQuery performance with table storage5 minutes
What are aggregations and why use them?5 minutes
Creating an aggregation5 minutes
Module summary: Optimize a model for performance in Power BI7 minutes

12 readingsTotal 145 minutes

Exercise: Improving data model performance30 minutes
Exemplar: Improving data model performance10 minutes
Optimizing columns and metadata10 minutes
Optimizing the Auto date/time feature10 minutes
Activity: Optimizing the columns and Auto date/time10 minutes
Additional resources: Optimize performance in a Power BI model5 minutes
Walk-through: Optimizing a DirectQuery model10 minutes
Additional resources: Optimize DirectQuery models5 minutes
Exercise: Adding an aggregation30 minutes
Exemplar: Adding an aggregation10 minutes
How to manage aggregations step-by-step 10 minutes
Additional resources: Create and manage aggregations5 minutes

6 assignmentsTotal 95 minutes

Module quiz: Optimize a model for performance in Power BI30 minutes
Self-Review: Improving data model performance10 minutes
Knowledge check: Optimize a model for performance in Power BI15 minutes
Knowledge check: Optimize DirectQuery models15 minutes
Self-review: Adding an aggregation10 minutes
Knowledge check: Create and manage aggregations15 minutes

1 discussion promptTotal 10 minutes

How would performance and optimization impact different stakeholders?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.