This course is designed to provide a comprehensive foundation in Microsoft Data Analytics, equipping learners with essential skills in Power BI for data-driven decision-making. Participants will begin by exploring data sources, understanding how to connect, manage, and optimize various datasets for analysis.

The course progresses to data cleaning techniques, ensuring accuracy and consistency in raw data before visualization. Learners will gain expertise in data types and data combining, enhancing efficiency in integrating multiple datasets. Additionally, the course covers data transformation principles, allowing participants to refine and manipulate data for advanced modeling and reporting. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical insights and hands-on practice. Participants will engage with approximately 3:00–4:00 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to test the ability of learners in real-world scenarios. Module 1: Microsoft Data Analytics: Exploring Power BI Data Sources Module 2: Data Cleaning Techniques in Power BI Module 3: Data Types and Transformation Techniques in Power BI At the end of the course, learners will learn - Understand key concepts of the PL-300 certification and the role of a data analyst. - Learn to acquire, clean, and transform data using Power BI tools. - Develop proficiency in Power BI’s interface, modeling, and visualization. - Learn to manage columns and reduce rows for efficient data cleaning in Power BI. - Apply sorting, splitting, and replacing values to enhance dataset organization. - Utilize filters, including text, numerical, and date-based, for refined data analysis. - Develop practical skills for transforming raw data into structured insights in Power BI. - Understand different Power BI data types and their applications in data processing. - Learn to merge, append, and integrate datasets using various query techniques. - Apply transformation techniques like grouping, transposing, pivoting, and unpivoting for structured analytics. - Develop practical skills in error handling, renaming, and optimizing data workflows in Power BI This course is for Data Analysts, Data Engineers, Power BI Analyst, and Power BI Experts