DA-100: Microsoft Power BI, Part 2 of 5: Data Transformation

Course description

Data Science is a growing field, this second course in the series digs into the Query Editor and Advanced Transformations. Data Analysts are responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations. The DA-100 Exam validates this expertise.

Each LearnNowOnline training course is made up of Modules (typically an hour in length). Within each module there are Topics (typically 15-30 minutes each) and Subtopics (typically 2-5 minutes each). There is a Post Exam for each Module that must be passed with a score of 70% or higher to successfully and fully complete the course.

Prerequisites

Experience with Microsoft Excel, pivot tables and power pivot modelling is helpful.

Meet the expert

Nikolai Schuler

Nikolai is a mathematician and works as a data scientist in a large German company. He is focused mainly on gaining insights from data and creating a positive impact with this knowledge.

Video Runtime

268 Minutes

Time to complete

462 Minutes

Course Outline

Query Editor Module 1

Connecting to our Data Source (30:34)

• Introduction (00:08)
• Connecting to our data source (06:48)
• Editing and removing rows (08:10)
• Changing data types (08:24)
• Replace Values (03:27)
• Close & Apply (03:29)
• Summary (00:08)

Connecting Power BI to a csv file (24:21)

• Introduction (00:08)
• Connecting Power BI to a csv file (03:21)
• Connecting to a Web Page (05:04)
• Extract Characters (06:18)
• Splitting & Merging Columns (09:22)
• Summary (00:08)

Create a conditional column (32:09)

• Introduction (00:08)
• Create a conditional column (05:52)
• Columns from examples (08:38)
• Merging Queries (04:00)
• Joins (06:35)
• Apply the Knowledge (06:47)
• Summary (00:08)

Query Editor Module 2

Pivoting & Unpivoting (28:49)

• Introduction (00:08)
• Pivoting & Unpivoting (05:43)
• Appending Tables (08:20)
• Practice & Solution PopulationTable (14:30)
• Summary (00:08)

Fact Dimension Model (21:05)

• Introduction (00:08)
• Fact Dimension Model (09:19)
• Practice Load Dimension Table (03:48)
• Organizing our Queries in Groups (02:59)
• Entering data manually (04:43)
• Summary (00:08)

Creating an index column (25:53)

• Introduction (00:08)
• Creating an index column (03:04)
• Workflow & more transformations (04:38)
• Module Summary (05:05)
• Exercise 1 Instructions (01:41)
• Exercise 1 Solution (11:09)
• Summary (00:08)

Advanced Transformation

Advanced Editor - Best practise (23:20)

• Introduction (00:08)
• Advanced Editor - Best practise (08:43)
• References vs. Duplicates (09:50)
• Enable Disable Load & Report Refresh (04:31)
• Summary (00:08)

Group by (24:33)

• Introduction (00:08)
• Group by (04:47)
• Mathematcal Operations (04:54)
• Run R Script (14:36)
• Summary (00:08)

Using Parameters to transform data (12:10)

• Introduction (00:08)
• Using Parameters to transform data (06:28)
• Exercise 2 Instructions (00:55)
• Exercise 2 Solution (04:31)
• Summary (00:08)

Understanding relationships (17:28)

• Introduction (00:08)
• Understanding relationships (05:07)
• Create & Edit relationships (06:16)
• One-to-Many and One-to-One Relationship (05:49)
• Summary (00:08)

Many-to-Many relationship & Crossfilter direction (14:27)

• Introduction (00:08)
• Many-to-Many relationship & Crossfilter (08:15)
• Cross filter direction (05:56)
• Summary (00:08)

ActivateDeactivate Relationships (13:16)

• Introduction (00:08)
• ActivateDeactivate Relationships (05:52)
• Create Model Summary (03:04)
• Exercise 3 - Create Model (02:27)
• Exersice 3 - Solution (01:37)
• Summary (00:08)