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Microsoft Power BI for Beginners
Learn Data Preparation, Analysis and Visualization | Build Powerful Dashboards using Power BI Desktop

This Course Includes
udemy
0 (0 reviews )
1.5 total hours
english
Online - Self Paced
course
Udemy
About Microsoft Power BI for Beginners
If you are looking to learn Power BI from scratch or improve your existing skills, this course will provide you with the necessary reporting tools and skills to create your first dashboard using Microsoft Power BI. It is designed to cater to learners of beginner level as it will cover everything related to cleaning and transforming datasets, building relationships between data tables, creating common DAX calculations, and using powerful visualizations for analysis.
The course will cover 3 main parts:
Part 1: Creating Visualizations
Introduction to Power BI Desktop: Download and install the software.
Common visualizations: Learn how to create various chart types, including drill down and conditional formatting
Part 2: Get and Transform Data in Power Query Editor
Data cleaning and preparation: Learn how to import, clean and prepare data
Data transformation: Learn how to transform text, numbers, dates, and times, and create custom columns
Part 3: Refining the Model
Data relationships: Discover how to establish relationships between multiple tables in your data model.
DAX calculations: Learn how to create custom columns and measures using the DAX language to perform calculations and derive insights from your data.
This course will provide you with a solid foundation in Power BI, covering the core concepts and skills
What You Will Learn?
- Equipt students with hands-on experience of business intelligence tools leveraged by data analysts and data scientist.
- Understand the capabilities and use cases of Power BI.
- Acquire data from various sources and create robust data models.
- Desgin and build visually appealing and informative reports and dashboards.
- Perform advanced data analysis and create custom calculations for deeper data insights, commonly used by data scientists.