This module, "Operations on Multiple Tables," covers essential techniques for handling and analyzing data across multiple tables. By delving into different cleaning techniques, students will gain proficiency in efficiently retrieving datasets that can be directly used for visualizations. The module goes beyond theoretical concepts by providing practical exercises using a real-world case study, allowing users to apply their problem-solving abilities in a hands-on manner. At the end of this module, students will discover how to enhance data models by gaining an understanding of Fact tables and Dimension tables. Upon completion of the module, students will be able to acquire the skills to effectively perform operations on multiple tables, ensuring clean, transformed, and relationship-driven data models for analysis.

In this module "DAX Operator", students will gain valuable skills to perform advanced calculations and data manipulations in Power BI. Students will explore various DAX functions and operators, understand their syntax and structure, and learn how to apply them effectively in Power BI. Additionally, they will also differentiate between calculated columns and measures, gaining insights into when to use each approach. In the end, students will have an in-depth understanding of the Row context and Filter context. Through practical examples and problem-solving exercises, students will develop a solid understanding of DAX fundamentals and their significance in data analysis.

In this module, students will delve deeper and acquire skills and knowledge to create comprehensive reports and expanding their knowledge of utilizing DAX operators. They will learn essential skills to utilize diverse visualizations and address problem statements to deliver actionable insights. Furthermore, this module will emphasize the importance of designing and structuring the report to make it relevant for businesses. By mastering these skills, students will acquire the necessary tools to become an expert in the field of business intelligence and contribute to data-driven decision-making.