Become a BI Developer with Power BI & SQL Server

The Business Intelligence (BI) Developer Program at Gyanlytics Academy is designed for aspiring data professionals who want to build strong expertise in data modeling, reporting, and analytics using Power BI and SQL Server. This program combines database fundamentals with advanced visualization techniques to help you deliver end-to-end BI solutions.

📚 What You Will Learn

🔹 SQL Server (Advanced & Enterprise-Level)

• Core & Intermediate SQL

• • Joins, Subqueries, CTEs, and Nested Queries
    
    

  • Window Functions (RANK, DENSE_RANK, ROW_NUMBER, LEAD, LAG, NTILE)
    
    

  • Pivot, Unpivot, Grouping Sets, Rollup, Cube for reporting

• Advanced Database Design

• • Normalization vs. Denormalization
    
    

  • Primary, Foreign, Composite, and Unique Keys
    
    

  • Indexing strategies (Clustered, Non-Clustered, Covering Index, Filtered Index)
    
    

  • Constraints & Triggers

• Stored Procedures, Functions & Views

• • Advanced parameterized procedures
    
    

  • Table-valued vs. scalar functions
    
    

  • Indexed views for performance

• Performance Tuning & Query Optimization

• • Execution plans & query hints
    
    

  • Statistics and Index maintenance
    
    

  • Handling Deadlocks & Locks
    
    

  • Optimizing queries for millions of rows

• Transactions & Error Handling

• • ACID properties & transaction management
    
    

  • Nested transactions
    
    

  • TRY…CATCH, THROW for robust error handling

• Enterprise-Level Features

• • Partitioned tables & indexes for large data sets
    
    

  • SQL Server Agent jobs for scheduling ETL tasks
    
    

  • Temp tables vs. Table variables
    
    

  • Recursive CTEs for hierarchical data
    
    

  • Dynamic SQL for flexible queries

• ETL Foundations with SQL Server

• • Data Staging and Transformation best practices
    
    

  • Integration with SSIS for automation workflows (introductory level)

🔹 Power BI (Advanced – Enterprise & Expert Level)

• Data Modeling

• Star Schema vs. Snowflake Schema – pros & cons in BI
  
  

• Handling Slowly Changing Dimensions (SCD Types 1, 2, 3)
  
  

• Composite Models (DirectQuery + Import)
  
  

• Incremental Refresh for large datasets
  
  

• Aggregation tables for performance optimization
  
  

• Calculation Groups (Tabular Editor) for advanced time intelligence
  
  

• Best practices for large-scale semantic models
  
  

• DAX Mastery

• Advanced Time Intelligence (Rolling Averages, YOY, MTD/QTD/YTD, Fiscal Calendars)
  
  

• Parent-Child hierarchies with PATH functions
  
  

• Dynamic Measures & Titles (using SELECTEDVALUE & SWITCH)
  
  

• What-If parameters for scenario analysis
  
  

• Calculation Groups for reusable logic
  
  

• Optimizing DAX with variables & performance analyzer
  
  

• Complex DAX patterns (Cohort Analysis, Market Basket Analysis, Customer Segmentation)
  
  

• Dashboard Design & Best Practices

• Executive KPI Dashboards with drill-through navigation
  
  

• Dynamic Visuals (conditional formatting with DAX)
  
  

• Tooltip Pages for advanced context
  
  

• Custom Visuals (KPI Indicators, Sankey, Network Graph, Bullet Charts, etc.)
  
  

• Report Themes & Branding for corporate identity
  
  

• Bookmarking & storytelling techniques for presentations
  
  

• Accessibility standards in dashboards (for inclusivity)
  
  

• Security & Governance

• Row-Level Security (RLS) – Static & Dynamic
  
  

• Object-Level Security (OLS) – securing sensitive columns/tables
  
  

• Workspace Governance & Role Assignments
  
  

• Sensitivity Labels for compliance (GDPR, HIPAA)
  
  

• Auditing & Usage Metrics for monitoring reports
  
  

• Shared & Certified Datasets – Single Source of Truth
  
  

• Enterprise BI Features

• Power BI Service: Workspaces, Apps & Deployment Pipelines (Dev → Test → Prod)
  
  

• Data Refresh Scheduling & On-Premises Gateway Configuration
  
  

• Incremental Load Strategies for large data models
  
  

• Paginated Reports with Power BI Report Builder (SSRS replacement)
  
  

• Composite models for hybrid data connectivity
  
  

• Power BI + Azure Synapse / Data Lake for enterprise-scale BI
  
  

• Large dataset storage format (Premium Gen2)
  
  

• Real-Time and Advanced Integration

• Real-time dashboards using DirectQuery & Streaming datasets
  
  

• Integration with Azure Stream Analytics / Event Hub / IoT Hub
  
  

• Embedding Power BI Reports in web apps & portals (Power BI Embedded)
  
  

• Power BI + Python & R for advanced analytics & forecasting
  
  

• Power BI + Power Automate for automated workflows (scheduled exports, alerts, triggers)
  
  

• AI-powered visuals: Key Influencers, Decomposition Tree, Smart Narratives
  
  

• Integration with Excel, SharePoint, and Microsoft Teams
  
  

• Performance Optimization & Scaling

• Performance Analyzer for slow visuals
  
  

• Query Diagnostics for bottleneck detection
  
  

• Relationship & Cardinality optimization
  
  

• Large dataset management with aggregations & partitions
  
  

• Best practices for enterprise report publishing
  
  

• Dataset size reduction techniques (compression, encoding, incremental refresh)
  
  

• Monitoring dataset refresh failures & error handling

🎯 Program Outcomes

• Gain practical knowledge of SQL Server + Power BI integration
  
  

• Build automated dashboards for real-world business problems
  
  

• Learn to design end-to-end BI solutions from raw data to insights
  
  

• Be job-ready as a BI Developer / Data Analyst in top organizations

👉 Career Path: BI Developer | Data Analyst | SQL & Power BI Specialist