Mastering DAX And Data Models In Power BI Desktop

Name: Mastering DAX And Data Models In Power BI Desktop
Rating: 4.4 (97 reviews)
Author: Abhay Gadiya

Learn Data Modelling, Relationship, and DAX language in Power BI from scratch.

updated on icon Updated on Apr, 2024

language icon Language - English

person icon Abhay Gadiya

English [CC]

category icon Office Productivity,Microsoft Power BI

Lectures -54

Resources -1

Duration -5.5 hours

4.4 ★★★★ ★

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Course Description

Mastering DAX and Data Models in Power BI Desktop helps you grasp different data analytics concepts if you intend to start using Power BI and embark on a data analytics journey.

In my course named Power BI Query Editor - Master Data Transformation, I have discussed ETL procedures. It contains more than 6 hours of video explaining every Power Query and M Language subject with the use of actual datasets.

After completing the aforementioned course, you must proceed to the following level for DAX, relationships, and data modeling.

Mastering DAX And Data Models in Power BI Desktop Overview

This online course will go through the following concepts in detail:

Gathering the data - Perform your Extract > Transform > Load (ETL) activities.
Model your data - Normalize your data is one of the critical steps
Relationship between data tables - To understand the flow of information
DAX - Perform your data crunching and analysis
Visual analytics - Not just numbers but pictorial presentation

Presently, many courses only briefly touch on data modeling and relationships and only explain DAX. To achieve optimum performance in your reports and keep a low degree of complexity in your DAX formulas, effective data organization is crucial.

Gathering data "as is" from a data source, defining relationships, and then starting to construct reports are the simplest ways to create a data model in Power BI. Nevertheless, when you have an excessive number of tables or multiple granularity levels, this strategy raises a number of problems. This course will go into great detail on how to apply the basic principles of data normalization to develop appropriate data models.

It can be a bit difficult for someone just getting started with DAX because he may need to picture the outcome of the DAX formula he is creating in his head. This can be complex, so I've made a course where you'll explain how to use different DAX formulas in a straightforward and understandable manner. The many DAX concepts, such as filter context, row context, evaluation context, table or scalar DAX functions, iterator DAX functions, calculated measures, calculated columns, etc., will all be thoroughly explained in this course.

Who this course is for:

If you want to prepare for Microsoft Power BI certifications
students who have finished my Power BI Query editor course and want to understand more about DAX should take this course.
For anyone who wants to impress their stakeholders by automating management reporting.
Use DAX to complete your data analysis rapidly.

Goals

What will you learn in this course:

Establishing a basis for Power BI's data models, relationships, and DAX formulae
Different foundational data models and relationship ideas that are not addressed in any other course
Advantages and differences between normalized and de-normalized datasets
Three key guidelines for performing better while normalizing your dataset
Top Down, Star, and Snowflakes Schemas for Data Modeling
Relationship of one to many, many to one, many to one
Using a straightforward and understandable method, Power BI's complicated concepts are explained.
Complex DAX formulas include DAX Studio, DAX Variables, and Time Intelligence.

Prerequisites

What are the prerequisites for this course?

One should be aware of How to import and transform data into Power BI with the Query Editor
After completing my Power BI Query Editor course, this is the next step.
A person is eager to learn more about Power BI DAX ideas.
Verify that Power BI Desktop is installed in its most recent version.

Mastering DAX And Data Models In Power BI Desktop

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction to Data Modelling
17 Lectures

Data Modelling mindset - think in multiple tables 05:16 05:16
File Resources
Keys in Tables - Primary Key and Foreign Key 05:03 05:03
Introduction to Normalisation of Datasets 05:03 05:03
Rule # 1 : First Normal Form - single value and not repeating groups 05:16 05:16
Rule # 2 : Second Normal Form - composite primary key 06:19 06:19
Rule # 3 : Third Normal Form - dependency between non-key fields 05:37 05:37
How to normalize the a dummy dataset by applying normalization rules 13:13 13:13
Recap - Three Normalisation rules 03:01 03:01
Table types - Data / Fact table and Lookup / Dimension Table 05:58 05:58
Relationship Cardinality an introduction 01:50 01:50
One to Many relationship 02:48 02:48
Many to Many relationship 02:22 02:22
One to One relationship 01:45 01:45
Relationship cardinality recap 01:46 01:46
Relationship in Power BI - Active / In-active, one / both way filter propagation 14:50 14:50
Diagram view : Top Down, Star Schema, Snow Flakes - managing table presentation 05:49 05:49