Module 1
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Introduction to Power BI
What is Power BI, components (Desktop, Service, Mobile), real-world BI use cases and end-to-end Power BI workflow: Extract → Transform → Visualize → Share.
Practical Data Analytics curriculum focused on Power BI and SQL: extract, transform, model, visualize and share business insights.
What is Power BI, components (Desktop, Service, Mobile), real-world BI use cases and end-to-end Power BI workflow: Extract → Transform → Visualize → Share.
System requirements, installing Power BI Desktop and exploring Home, Report, Data and Model views for report development.
Connect to Excel, CSV, SQL Server, Web APIs and Azure; Import vs DirectQuery; credentials, data connection management and refresh scheduling.
Power Query Editor basics: rename/change types, remove duplicates, merge/append queries, pivot/unpivot, handle nulls and advanced transformations.
Fact vs Dimension tables, star/snowflake schemas, relationships, cardinality, cross-filter direction, calculated columns and measures.
Basic DAX functions (SUM, AVERAGE, COUNT), logical functions, date/time functions, text and statistical functions, filter functions and time intelligence (TOTALYTD, SAMEPERIODLASTYEAR).
Core visuals (bar, line, pie, table), advanced visuals (treemap, funnel, gauge, maps), custom visuals from AppSource, interactions, slicers and drillthroughs.
Multi-page reports, dashboard design, formatting, themes, color schemes, tooltips, bookmarks, buttons and storytelling with visuals.
Publish reports to Power BI Service, datasets vs reports vs dashboards, workspaces, sharing, permissions, collaboration and commenting.
Hands-on project: connect to dataset, prepare and clean data, create calculations and visuals, build an interactive dashboard and publish to Power BI Service.
Database fundamentals, relational models, SQL Server overview, installing SQL Server/SSMS and classification of SQL commands.
Data types, DDL/DML statements, SELECT queries, type conversion and running basic SQL queries for data retrieval and manipulation.
Filtering using WHERE, ORDER BY sorting, GROUP BY/HAVING for aggregation, and common aggregate functions for analytical queries.
Understand multi-table queries, INNER/LEFT/RIGHT/FULL joins, primary/foreign keys and writing join queries for reporting and analysis.
Subqueries, transaction control (SAVE, COMMIT, ROLLBACK), privileges, and advanced queries including window functions and control statements.
Create user-defined functions, stored procedures (IN/OUT params), triggers, views for reusable queries, and understand indexes and performance optimization techniques.
Write single/multiple CTEs, recursive CTEs, use CTEs with aggregation and joins, and apply SQL functions for transformations.
Integrating SQL Server with AI tools, using AI for query generation/optimization, data import/export, and handling noisy or missing data.
End-to-end analytics project combining SQL data prep and Power BI reporting: build, publish and present an interactive dashboard with insights.
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