Power BI: Data Analytics and Data Preparation

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Overview

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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

Syllabus

Microsoft Data Analytics: Exploring Power BI Data Sources

This module provides a comprehensive understanding of Power BI and data analytics, focusing on key concepts, tools, and exam preparation strategies for PL-300 certification. It emphasizes the principles of data-driven decision-making, data modeling, and visualization techniques, fostering a strong foundation for practical implementation. Participants will gain valuable insights into Power BI’s capabilities, installation, and user interface, enabling them to connect and transform data from various sources like Excel, CSV, and Web using Power Query Editor. The module also covers roles in the data world, responsibilities of a data analyst, and best practices for preparing for the certification exam. By the end of this module, learners will be equipped with the technical knowledge and skills required to navigate Power BI, analyze datasets effectively, and apply industry-standard practices for real-world data analytics solutions.

Data Cleaning Techniques in Power BI

This module provides a comprehensive understanding of data cleaning techniques in Power BI, ensuring datasets are properly structured for analysis and visualization. Participants will explore managing columns, reducing rows, and applying sorting and filtering operations to refine data integrity. The module covers advanced transformation techniques, such as splitting columns, replacing values, and applying text, numerical, and date-based filters for enhanced accuracy. By the end of this module, learners will gain hands-on expertise in organizing, filtering, and preparing data efficiently within Power BI to drive better analytical insights.

Data Types and Transformation Techniques in Power BI

This module provides a comprehensive understanding of Power BI data types, data integration techniques, and advanced data transformation strategies. Participants will learn to classify numerical, date, text, boolean, and binary data types, ensuring structured and optimized data processing within Power BI. Additionally, learners will explore data combination techniques, including merge queries, inner joins, and append queries, allowing for seamless integration across multiple datasets. The module further delves into data transformation principles, covering grouping, transposing, pivoting, unpivoting, and various row operations, helping users refine data models for accurate insights. By the end of this module, participants will have hands-on expertise in transforming raw data into structured formats, enabling effective analytics, reporting, and visualization within Power BI.