📊 Power BI Syllabus

This syllabus outlines the complete learning path for the Power BI module, broken down into 15 focused chapters for easier study preparation.

Part 1: Fundamentals & Ingestion

🏢 01 - Introduction to Power BI

📊 Business Intelligence and Data Visualization 💡 What Power BI is and why it is used (Features, benefits, and applications) 🥊 Power BI vs Tableau, Qlik Sense and Looker 🔑 Power BI licensing: Free and Pro 📁 Power BI files: .pbix and .pbit ☁️ Power BI Desktop vs Power BI Service 🛠️ Power Query, Power Pivot, Power View, Power Map and Power Q&A 🧱 Building blocks: Dataset/Semantic Model, Visualization, Report, Dashboard and Tile 📈 Reports vs Dashboards 🏗️ Power BI architecture: Data Integration → Transformation → Modelling → Reporting → Publishing → Dashboard ⚙️ Power BI Desktop installation and interface 🔄 Complete workflow: Connect → Transform → Model → Calculate → Visualize → Publish → Share

🔌 02 - Data Connectivity and Storage Modes

📄 Excel, CSV, text files and folders 🗄️ SQL and other databases (Databricks, Azure, Power Platform) 🌐 Online services, OData feeds, Web, APIs, and Blank Queries 🐘 Hadoop, Exchange and Active Directory 🔌 Connecting, previewing and loading data 📥 Import Mode 📡 DirectQuery Mode 🧩 Composite Models and Dual Storage Mode 🟢 Live Connection 🥊 Import vs DirectQuery vs Composite vs Live Connection (Advantages, limitations, use cases)

🧹 03 - Power Query and Data Cleaning

🛠️ What Power Query and Power Query Editor are 🔄 Extract, Transform and Load (ETL) process 📋 Queries, Data Preview, Query Settings and Applied Steps ✅ Column Quality (Valid, error, empty, unknown and unexpected values) 📈 Column Distribution and Column Profile (Top 1,000 rows vs entire dataset) 🗑️ Handle null/empty values and remove duplicates 🚨 Identify, remove and replace errors 🔠 Correct data types and trim/clean text 🏷️ Rename, remove, reorder, split, and merge columns 🔍 Filter and sort rows 🔢 Add index columns, Conditional columns, and Custom columns 📊 Group By and aggregation

🔀 04 - Combining and Reshaping Data

Merge Queries 🔗 Merge as a SQL JOIN operation ⬅️ Left Outer Join and ➡️ Right Outer Join 🔄 Full Outer Join and 🎯 Inner Join 🚫 Left Anti Join and Right Anti Join Append Queries ➕ Append as a SQL UNION operation 📚 Combining rows from multiple tables 🥊 Merge vs Append Reshaping 🔃 Transpose 🔄 Pivot ⤵️ Unpivot 🥊 Pivot vs Unpivot

Part 2: Modelling & Visualization

📐 05 - Data Modelling and Schemas

🧠 What a Power BI Data Model is ⭐ Importance of a good data model (understandability, performance, scalability) 🗂️ Tables, relationships, Primary keys, and Foreign keys Fact Tables 🛒 Business transactions, events, and measures Dimension Tables 🏢 Business entities, descriptive information, and filtering 🥊 Fact table vs Dimension table Data Model Types 🥞 Flat or Denormalized Schema ⭐ Star Schema ❄️ Snowflake Schema 🥊 Flat vs Star vs Snowflake Schema

🔗 06 - Relationships and Filter Flow

Cardinality 1️⃣ One-to-One 🌲 One-to-Many ⏪ Many-to-One 🕸️ Many-to-Many (Bridge tables) Relationship Behaviour 🟢 Active vs 🔴 Inactive relationships ⬇️ Single cross-filter direction vs ↔️ Bidirectional filtering 🌊 Downstream filter flow and Relationship ambiguity Best Practices ✅ Prefer Star Schema, one-to-many relationships, and single-direction filters 🚫 Avoid unnecessary many-to-many relationships and bidirectional filters 🔼 Keep dimension tables above fact tables 🙈 Hide technical fields and foreign keys

📈 07 - Core Data Visualizations

👁️ Importance of data visualization and selecting the correct chart 📖 Data storytelling and avoiding misleading visuals Comparison 📊 Bar Chart and Column Chart (Clustered vs Stacked) Trends 📉 Line Chart 🌊 Area Chart (Stacked Area Chart) 🎀 Ribbon Chart (Rank changes and trends over time) Composition and Process 🍕 Pie Chart and Donut Chart 🌳 Tree Map 🌊 Waterfall Chart (Positive and negative contributions) 🌪️ Funnel Chart (Process stages, conversion and bottleneck analysis) Relationships, Distribution, and Geographic 🎯 Scatter Chart, Bubble Chart, and 🔥 Heat Map 🗺️ Map and Filled Map (Location-based analysis)

🎛️ 08 - Advanced Visuals and Interactivity

Business Visuals ⏱️ Gauge and KPI (Actual value, target value and trend) 📊 Table vs Matrix (Hierarchies, drill-down and subtotals) 📇 Card and Multi-Row Card (Callout values and category labels) 🌳 Decomposition Tree (Root-cause and AI-based analysis) Report Interactivity ✂️ Slicers and interactive filtering (List, dropdown, date, range, hierarchy) 🔍 Visual-level, Page-level, and Report-level filters ⏬ Drill down, drill up, and Drill through 💬 Tooltips, Bookmarks, Buttons, and page navigation 🔄 Visual interactions, report formatting, and themes

Part 3: DAX Formulas

🧮 09 - Introduction to DAX

🧠 What DAX is (syntax, expressions and functions) 🗂️ Table, column and measure references ➕ Arithmetic, comparison, logical and text operators DAX Context 📏 Row Context 🔍 Filter Context (Filters from visuals, slicers and relationships) 🥊 Row Context vs Filter Context and Context Transition DAX Calculation Types 🔢 Calculated Columns (Row-level calculations, stored in data model) 🗂️ Calculated Tables (Create new tables using existing data) ⚡ Measures (Dynamic calculations evaluated using Filter Context) 👻 Implicit Measures vs Explicit Measures 🥊 Calculated Columns vs Measures vs Calculated Tables

🔢 10 - Core DAX Functions

Aggregation ➕ SUM(), AVERAGE(), MIN(), MAX(), DIVIDE() Count 🔢 COUNT(), COUNTA(), COUNTROWS(), DISTINCTCOUNT() Logical 🧠 IF(), SWITCH(), AND(), OR(), NOT()

🔧 11 - Modifying DAX Context

Context Modification 🎯 CALCULATE() and modifying Filter Context 🔍 FILTER() and table filtering 🌐 ALL() and removing filters Table and Relational Functions 🔗 VALUES() 🔗 RELATED() 🔗 USERELATIONSHIP()

⏱️ 12 - Iterators and Time Intelligence

Iterator and Ranking Functions 🔄 Iterator functions and row-by-row calculations 🧮 SUMX(), AVERAGEX(), MINX(), MAXX(), COUNTX() 🥊 SUM() vs SUMX() 🏆 RANKX() and TOPN() (Top products and customer analysis) Date and Time Intelligence 📅 Date tables, calendar tables, and date hierarchies ⏳ DATE(), YEAR(), MONTH(), DAY(), TODAY(), NOW() 📈 YTD, MTD, QTD (Year/Month/Quarter to Date) ⏪ Previous-period analysis (Year-over-Year, Month-over-Month growth) 📊 Running totals and cumulative calculations DAX Best Practices ✅ Prefer explicit measures, reuse measures, and use fully qualified references 🚫 Minimize expensive iterator functions and unnecessary calculated columns

Part 4: Service, Security & Deployment

☁️ 13 - Power BI Service and Collaboration

☁️ Cloud-based analytics (Desktop vs Service) 🚀 Publishing reports and managing semantic models 🤝 Collaboration, sharing, and Microsoft Teams integration Workspaces 🗂️ Creating and organizing workspaces 👤 Workspace Roles: Admin, Member, Contributor, Viewer 🛡️ Role permissions and Least-privilege principle Dashboards and Apps 📈 Creating dashboards, pinning visuals, and real-time tiles 💬 Dashboard Q&A 📦 Power BI Apps (Bundling reports and dashboards) 🛠️ Configuring app permissions, audiences, and read-only distribution

🔐 14 - Security, Refresh, and Deployment

Data Refresh and Gateway 🔄 Manual, on-demand, and scheduled refresh 🔑 Data-source credentials and troubleshooting failures 🚪 On-Premises Data Gateway (connecting cloud to on-prem) Data Security and RLS 🔐 Row-Level Security (RLS) vs Object-Level Security (OLS) 🎭 Static RLS vs Dynamic RLS ⚙️ Creating roles and DAX security filters (USERNAME(), USERPRINCIPALNAME()) 👁️ View as Role and assigning users/security groups Alerts and Optimization 🚨 Creating data alerts, KPI monitoring, and Power Automate integration ⏱️ Performance Analyzer and reducing model size ⚡ Optimizing DAX, query folding, and improving DirectQuery performance Deployment Pipelines 🛠️ Development, Testing, and Production environments 🚀 Deploying Power BI content and controlled releases

Part 5: Capstone

💻 15 - End-to-End Mini Project

🔗 1. Connect Product, Customer and Transaction data 🧹 2. Clean and transform data using Power Query 🔠 3. Handle nulls, duplicates, errors and data types 🔄 4. Merge, append, pivot and unpivot data 🗂️ 5. Create Fact and Dimension tables and build a Star Schema 🔗 6. Create relationships and a Date table 🧮 7. Create Sales, Revenue, Profit, Orders and Customer measures 📈 8. Create YTD, MTD, growth, ranking and Top-N measures 📊 9. Build KPI, Sales, Product and Customer reports 🗺️ 10. Add charts, tables, matrices, maps, slicers, and drill-downs ☁️ 11. Publish to Power BI Service and create a dashboard 🔐 12. Configure workspace access and apply Row-Level Security 🚪 13. Configure Gateway and Scheduled Refresh 📦 14. Create a Power BI App and Deploy through Deployment Pipelines

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