Module 1: Introduction to Microsoft Power BI 

• Overview of Business Intelligence (BI) and Power BI’s role in modern analytics 

• Key features and components of Power BI: Power BI Desktop, Power BI Service, and Power BI Mobile 

• Understanding the Power BI workflow: connecting data, transforming data, visualizing, and sharing insights 

• Installing and setting up Power BI Desktop 

Module 2:  Connecting to Data Sources 

• Overview of different data sources: Excel, SQL Server, SharePoint, cloud-based data, APIs 

• Connecting Power BI to multiple data sources (databases, online services, files) 

• Working with live connections vs. import mode 

• Scheduling data refreshes in Power BI 

• Managing data connections and gateway setup for on-premise data 

Module 3: Data Transformation with Power Query 

• Introduction to Power Query and its role in data preparation 

• Cleaning, transforming, and combining data using the Power Query Editor 

• Handling missing data, removing duplicates, filtering, and grouping data 

• Using M code for advanced data transformations in Power Query 

• Best practices for optimizing query performance 

Module 4: Data Modeling in Power BI 

• Introduction to data modeling and relationships 

• Creating and managing relationships between tables 

• Working with data hierarchies (time, geography, product categories) 

• Creating calculated columns and measures using Data Analysis Expressions (DAX) 

• Advanced DAX functions for time intelligence, filtering, and aggregations 

Module 5: Creating Interactive Reports and Dashboards 

• Designing effective data visualizations using Power BI’s built-in visuals (charts, tables, maps) 

• Adding slicers, filters, and drill-through options for interactivity 

• Creating custom visuals in Power BI 

• Using bookmarks, buttons, and tooltips to enhance user experience 

• Best practices for designing responsive dashboards for mobile and desktop users 

Module 6: Power BI Service: Sharing and Collaboration 

• Publishing reports and dashboards to the Power BI Service 

• Creating and managing workspaces for collaboration 

• Sharing reports with colleagues and setting access permissions 

• Understanding Power BI Pro and Power BI Premium licensing 

• Embedding Power BI reports in websites, apps, and Microsoft Teams 

Module 7: Advanced DAX for Data Analysis 

• Deep dive into DAX (Data Analysis Expressions) for complex calculations 

• Writing calculated measures, calculated tables, and custom columns 

• Time intelligence functions for comparing data over time (YTD, QTD, MTD) 

• Context transitions and row vs. filter context in DAX 

• Debugging DAX formulas and performance optimization 

Module 8: Power BI Dataflows and ETL (Extract, Transform, Load) 

• Introduction to Power BI Dataflows and their role in data preparation 

• Setting up dataflows for reusability and consistency across reports 

• Automating data transformation processes using dataflows 

• Integrating Power BI with other ETL tools like Azure Data Factory and SSIS 

• Managing large datasets and incremental data loads 

Module 9: Security in Power BI 

• Implementing row-level security (RLS) to restrict data access 

• Managing roles and permissions for different user groups 

• Data protection strategies in Power BI: encryption, auditing, and compliance 

• Power BI integration with Microsoft Information Protection (MIP) for data security 

• Best practices for securing Power BI reports and data 

Module 10: Performance Optimization in Power BI 

• Optimizing data models for faster performance 

• Best practices for reducing report load time 

• Using performance analyzer tools to identify bottlenecks 

• Managing large datasets in Power BI and using aggregations 

• Improving report rendering times and overall user experience 

Module 11: Power BI with Advanced Analytics 

• Integrating Power BI with Python and R for advanced analytics and machine learning 

• Performing statistical analysis using R/Python scripts in Power BI 

• Using AI visuals (Key Influencers, Q&A, Decomposition Tree) for data insights 

• Introduction to machine learning models in Power BI (AutoML in Power BI Premium) 

• Visualizing predictive analytics models in Power BI dashboards 

Module 12: Capstone Project: Building a Power BI Solution 

• Design and implement a complete Power BI solution from data sourcing to reporting 

• Connect to real-world datasets and transform them using Power Query 

• Build a data model with relationships, calculated columns, and DAX measures 

• Create an interactive dashboard with drill-throughs, slicers, and custom visuals 

• Publish the dashboard to Power BI Service and share it with stakeholders