Power BI Master Tutorial

Course Overview

Start
Introduction
Querying SharePoint Lists
Unpivot Columns
Copying and Pasting M Script
M Language Basics
Creating a Calendar Table with List.Dates
Adding Metadata with M Functions
Reusing Calendar M Script in Excel
Custom Query Functions
DATESYTD
DATESYTD and DATESMTD
DATEADD
DATESBETWEEN
Complicated Relationships
Granularity Discrepancies
Inactive Relationships
Many to Many
Introduction
Filter Context Flows Downstream
Order of Operations
ALL to Clear Structural Filters
ALL - Choosing the Right Table
FILTER
Disconnected Tables
Lab Results
Disconnected Visuals
Row Level Security
Custom Visuals
Republish Dashboard
Excel Objects in Power BI Online
Designing for Mobile
Using the Power BI Mobile App
Alerts
Conclusion

(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
Learners can learn from Power BI Master Tutorial in the following areas:

1. Querying SharePoint Lists: Learners can learn how to query SharePoint lists and use them to create data models. They can also learn how to use M Script to copy and paste data, as well as the basics of M Language.

2. Relationships and Filters: Learners can learn how to create relationships between tables, and how to use filter context to flow data downstream. They can also learn how to use ALL to clear structural filters, and how to use the FILTER function to create disconnected tables.

3. Custom Visuals and Mobile Design: Learners can learn how to create custom visuals, republish dashboards, and use Excel objects in Power BI Online. They can also learn how to design for mobile and use the Power BI Mobile App, as well as how to set up alerts.

[Applications]
After completing this course, users of Power BI can apply their knowledge to create custom queries, use M language to add metadata, create calendar tables, and design for mobile. They can also use the Power BI Mobile App to set up alerts and republish dashboards. Additionally, they can use disconnected tables and visuals, as well as apply filter context and row level security.

[Career Paths]
1. Business Intelligence Analyst: Business Intelligence Analysts are responsible for collecting, analyzing, and interpreting data to help inform business decisions. They use a variety of tools, such as Power BI, to create reports and dashboards that provide insights into the performance of the business. As businesses become increasingly data-driven, the demand for Business Intelligence Analysts is expected to grow.

2. Data Scientist: Data Scientists use a variety of tools and techniques to analyze large datasets and uncover patterns and trends. They use Power BI to create visualizations and reports that help them to better understand the data and make informed decisions. As businesses become more reliant on data, the demand for Data Scientists is expected to increase.

3. Data Visualization Designer: Data Visualization Designers use Power BI to create visually appealing and informative dashboards and reports. They use their knowledge of design principles and data visualization techniques to create visuals that are both aesthetically pleasing and informative. As businesses become more reliant on data, the demand for Data Visualization Designers is expected to increase.

4. Power BI Developer: Power BI Developers are responsible for developing and maintaining Power BI solutions. They use their knowledge of Power BI and the M language to create custom visuals, queries, and reports. As businesses become more reliant on data, the demand for Power BI Developers is expected to increase.

[Education Paths]
1. Bachelor of Science in Business Analytics: This degree path focuses on the development of analytical skills and the application of data-driven decision making. It covers topics such as data mining, predictive analytics, and machine learning. This degree is becoming increasingly popular as businesses are recognizing the value of data-driven decision making.

2. Master of Science in Data Science: This degree path focuses on the development of data science skills and the application of data-driven decision making. It covers topics such as data mining, predictive analytics, machine learning, and artificial intelligence. This degree is becoming increasingly popular as businesses are recognizing the value of data-driven decision making.

3. Master of Science in Business Intelligence: This degree path focuses on the development of business intelligence skills and the application of data-driven decision making. It covers topics such as data mining, predictive analytics, machine learning, and artificial intelligence. This degree is becoming increasingly popular as businesses are recognizing the value of data-driven decision making.

4. Master of Science in Data Analytics: This degree path focuses on the development of data analytics skills and the application of data-driven decision making. It covers topics such as data mining, predictive analytics, machine learning, and artificial intelligence. This degree is becoming increasingly popular as businesses are recognizing the value of data-driven decision making.