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Power BI

Course info – Power BI is a powerful business analytics tool developed by Microsoft. It allows users…

  • 19
  • 45 Days
  • 0
  • (0)

Course info –

Power BI is a powerful business analytics tool developed by Microsoft. It allows users to connect to various data sources, transform and model data, and create interactive visualizations and reports.

What will you learn?

As a power BI developer, you work on tasks such as:

  • Analyze data from multiple sources like Excel, databases, or cloud services.
  • Create dashboards and reports with drag-and-drop simplicity.
  • Share insights across teams or embed them into apps.
  • Use AI features to uncover trends and patterns in your data.

Power BI is widely used across industries for data analysis and decision-making. It helps businesses track finances, forecast trends, and improve performance. In healthcare, it monitors patient data and enhances operational efficiency, while in retail, it provides insights into sales, customer behavior, and inventory management. Additionally, it supports sectors like education, manufacturing, IT, and marketing by offering tools to analyze and optimize processes effectively.

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Course Curriculum

Introduction to Power BI
Overview of Power BI and its capabilities Understanding the Power BI ecosystem Components of Power BI: Desktop, Service, and Mobile Latest Features and Updates in Power BI 2025 Power BI Licensing and Pricing Models

  • Overview of Power BI and its capabilities
  • Understanding the Power BI ecosystem
  • Components of Power BI: Desktop, Service, and Mobile
  • Latest Features and Updates in Power BI 2025
  • Power BI Licensing and Pricing Models

Power BI Data Sources and Connectivity
Connecting to various data sources (Excel, SQL Server, Azure, SAP, Web APIs, etc.) Working with cloud-based and on-premises data Understanding Direct Query, Import Mode, and Live Connection Connecting to real-time data streams and IoT data sources

Data Preparation and Transformation with Power Query
Introduction to Power Query and M Language Data cleansing, filtering, and transformation techniques Merging and appending queries Handling missing and duplicate data Implementing Incremental Loading in Power BI Optimizing Power Query transformations for performance

Data Modelling in Power BI
Understanding relational data modelling concepts Creating and managing relationships (One-to-One, One-to-Many, Many-to-Many) Working with calculated columns and measures Star Schema vs. Snowflake Schema Implementing aggregations and optimizing performance

Power Query Advanced Features
Advanced transformation techniques in Power Query Using Parameters and Custom Functions Query Folding and Performance Optimization Handling Large Datasets and Best Practices Debugging and Error Handling in Power Query

Data Visualization and Reporting
Creating interactive reports and dashboards Choosing the right visualization (charts, tables, maps, KPIs, etc.) Formatting and customizing reports Creating drill-through, slicers, and bookmarks for navigation Designing reports for different screen sizes (Mobile Optimization)

Power BI Desktop Advanced Features
Exploring Power BI Desktop interface and tools Using Query Editor for advanced transformations Best practices for designing scalable data models Utilizing performance analyzer for report optimization

Advanced Data Analysis with DAX
Introduction to Data Analysis Expressions (DAX) Writing DAX formulas for calculated columns and measures Implementing advanced calculations, time intelligence, and aggregations Understanding DAX variables and performance optimization

Power BI Service and Collaboration
Publishing reports to Power BI Service Sharing and collaborating on reports and dashboards Managing workspaces, apps, and permissions Scheduling data refresh and monitoring dataset performance

Power BI Security and Governance

Power BI Integration and Automation
Integrating Power BI with Microsoft tools (Excel, SharePoint, Teams, Power Automate, etc.) Automating data refresh and scheduled reporting Using Power BI APIs and embedding reports into applications Connecting with Azure Synapse Analytics and Data Lakes

AI-Powered Analytics in Power BI
Leveraging AI visuals (Key Influencers, Decomposition Tree, Q&A) Implementing machine learning models in Power BI Using Python and R scripts for advanced analytics

Power BI Best Practices and Optimization
Performance tuning for reports and dashboards Reducing dataset size and optimizing query performance Designing user-friendly and interactive dashboards Troubleshooting common errors and debugging techniques

Bonus: Hands-on Labs & Real-World Case Studies
End-to-end project implementation Building Incremental Data Load Pipelines Power BI best practices for large-scale enterprise solutions

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