Microsoft Power BI 3-day Course
Microsoft Power BI 3-day Course Outline
Looking for A Microsoft Power BI 3-day Course, Are you interested in learning how to use Power BI to analyze and visualize your data? Whether you’re a business professional looking to improve your data analysis skills or a student interested in learning more about data science, a Power BI online course can help you achieve your goals. In this article, we’ll provide an outline of what you can expect to learn in a typical Power BI online course. From the basics of data modeling and visualization to advanced topics like machine learning and predictive analytics, a Power BI course can help you develop the skills you need to succeed in a data-driven world. So, let’s dive in and explore what a Power BI online course has to offer!
Module 1: Introduction to Microsoft Data Analytics
This module examines the many jobs in the data arena, describes the critical tasks and responsibilities of a Data Analyst, and then examines the Power BI portfolio landscape.
Module 2: Data Collection in Power BI
This module investigates the identification and retrieval of data from diverse data sources. You’ll also learn about connectivity and data storage choices, as well as the differences and performance consequences of connecting directly to data vs importing it.
Module 3: Data Cleaning, Transformation, and Loading with Power BI
This subject will show you how to profile data and understand its state. They will learn how to spot anomalies, assess the quantity and structure of their data, and carry out the necessary data cleaning and transformation activities to prepare the data for loading into the model.
Module 4: Create a Power BI Data Model
This lesson covers the fundamentals of creating and developing a data model for optimal performance and scalability. This session will also assist you in understanding and dealing with several typical data modeling concerns, including relationships, security, and performance.
Module 5: Create Model Calculations in Power BI Using DAX
This session will expose you to the world of DAX and its actual capability for model enhancement. To tackle computation and data analysis challenges, you will learn about aggregations and the concepts of Measures, computed columns and tables, and Time Intelligence functions.
Module 6: Power BI Model Performance Optimization
The topic of this class introduces you to the methods, processes, ideas, and best practices for data modeling that are required to optimize a data model for enterprise-level performance.
Module 7: Create Power BI Reports
The content of this module exposes you to the essential concepts and principles of planning and producing a report, such as choosing the right graphics, creating a page layout, and implementing simple but crucial functionality. The critical problem of designing for accessibility is also addressed.
Module 8: Power BI Dashboard Design
This tutorial will teach you how to tell an engaging tale using dashboards and the various navigation options that are available. You will learn about features and functionality, as well as how to improve dashboard usability and insights.
Module 9: Recognize Power BI Patterns and Trends
This tutorial teaches you how to use extra elements to enrich the report for analytical insights into the data, as well as how to use the report for actual data analysis. You will also run advanced analyses on the report utilizing AI visualizations for even deeper and more relevant data insights.
Module 10: Power BI Workspace Creation and Management
The content of this class will teach you about Workspaces and how to build and manage them. You will also learn how to share material, such as reports and dashboards, and how to publish an App.
Module 11: Power BI File and Dataset Management
This lesson will cover parameters and datasets. You’ll also discover how to manage datasets and parameters, create dynamic reports using parameters, and configure dataset refresh options.
Module 12: Row-level Security with Power BI
This module will teach you about row-level security, both static and dynamic approaches, and how to apply them.