• Gain advanced skills in navigating and utilizing the Power BI interface effectively, including the use of all essential features and tools. 

• Learn how to connect Power BI to a variety of data sources, including databases and Microsoft Excel, and manage data loading and preparation processes. 

• Understand how to create and manage complex data models, including the establishment of relationships between various data tables. 

• Develop the ability to write advanced DAX formulas for complex calculations, performance metrics, and time-based analysis, increasing your analytical capabilities in Power BI. 

• Learn how to create a range of advanced visualizations and customize them to better convey insights, utilizing best practices in data visualization. 

• Design and implement interactive dashboards that incorporate filters, slicers, and drill-through capabilities, enhancing user engagement and data exploration. 

• Leverage Power BI's AI features, including Quick Insights and Key Influencer visuals, to gain deeper analytical insights and predictive capabilities. 

• Understand how to publish and share reports via Power BI Service, manage workspaces, and collaborate with stakeholders effectively. 

• Learn to secure reports by implementing Row-Level Security (RLS) and understanding how to manage user permissions in the Power BI environment. 

• Apply concepts learned through practical exercises and case studies that simulate real-business scenarios, enhancing your ability to solve organizational data challenges. 

• Power BI Fundamentals: Participants should have prior experience with Power BI Desktop, including importing data, creating basic visuals, and building simple dashboards. Recommended course https://ohiocomputeracademy.com/courses/power-bi-for-beginners/ 

• Understanding of Basic DAX: Familiarity with calculated columns, measures, and basic DAX functions is beneficial. 

• Data Literacy: A basic understanding of data types, relationships, and business metrics will help in applying advanced analytics concepts. 

• Optional Excel Knowledge: Experience with Excel formulas or pivot tables can further enhance comprehension of Power BI calculations. 

This training will equip you for the following job roles and career paths:  

• Power BI Developer 

• Business Intelligence Analyst 

• Data Analyst 

• Power BI Consultant 

• Data Visualization Specialist 

Module 1: Recap of Power BI Desktop Interface 

• Overview of the Power BI Desktop workspace. 

• Understanding the different panes: Fields, Visualizations, and Reports. 

• Navigating the ribbon and available tools. 

Module 2: Connecting to Diverse Data Sources 

• Importing data from Excel, CSV files, SQL databases, and online services. 

• Connecting to Sharepoint. 

Module 3: Creating Complex Relationships Between Tables 

• Explanation of different types of relationships: one-to-one, one-to-many, and many-to-many. 

• Creating and editing relationships using the Model view. 

• Managing relationship direction and filtering implications. 

Module 4: Data Profiling Techniques Using Query Editor 

• Using Query Editor for data transformations: filtering, sorting, and cleaning data. 

• Analyzing data quality and profiling datasets in Power BI. 

• Techniques for data shaping and aggregation. 

Module 5: Advanced Calculations Using DAX 

• Key concepts of DAX: measures, calculated columns, and calculated tables. 

• Commonly used DAX functions: CALCULATE, FILTER, and TIME INTELLIGENCE functions. 

Module 6: Hierarchies and Drill-Down Reports 

• Creating hierarchies to improve data navigation in reports. 

• Implementing drill-down features in visualizations for deeper insights. 

Module 7: Visualizations 

• Overview of built-in visualizations and when to use them: bar charts, line charts, scatter plots, maps, and more. 

• Customizing visualizations for better presentation and analysis. 

• Best practices for effective data visualization. 

Module 8: Artificial Intelligence in Power BI 

• Using Quick Insights and AI visuals (e.g., Key Influencers, Decomposition Tree). 

• Introduction to integrating machine learning models into Power BI. 

Module 9: Power BI Service 

• Publishing reports to Power BI Service and sharing options. 

• Overview of workspaces, apps, and permissions management. 

• Collaborating with other users and co-authoring reports. 

Module 10: Securing Your Application 

• Data security measures: Row-Level Security (RLS) and permissions in the Power BI Service. 

• Understanding governance and compliance considerations when sharing data.