Fabric BI is Microsoft’s next-generation business intelligence platform within the Microsoft Fabric ecosystem. It unifies data integration, data engineering, data science, and BI into a single SaaS experience. It offers seamless collaboration, centralized governance, and AI-powered insights across the data pipeline. Learning Fabric BI opens doors to roles like BI Analyst, Fabric Consultant, and Cloud BI Developer.
✅ Data Factory Pipelines (ETL)
✅ Dataflow Gen2 Transformations
✅ Lakehouse & Warehouse
✅ Mapping, Wrangling, Alerts
✅ ETL Schedules & Triggers
✅ Security,FAUM, Activator
✅ Git Integration for CI/CD
✅ Power BI Integrations
✅ Real Time Project
✅ 1:1 Mentorship, Resume
Fabric BI
Training Course Contents:
Module 1 : Microsoft SQL (TSQL)
Ch 1: SQL SERVER INTRODUCTION
- Database Introduction
- Types of Databases
- Need for & ETL, DWH
- BI Implementations
- SQL Server Advantages
- Version, Editions of MSSQL
- Data Analyst Job Roles
Ch 2: SQL SERVER INSTALLATIONS
- SQL Server 2019, 2017
- SSMS Tools Installation
- Database Engine (OLTP)
- SCM, Configuration Tools
- Instance Types, Uses
- Authentication Modes
- Collation, File Stream
Ch 3: SQL BASICS – 1
- Need for Databases, Tables
- Need for SQL Commands
- DDL, DML & DQL Statements
- Database Creation @ GUI
- Data Operations @ GUI
- Session ID, SQL Context
- DB, Tables, Data @ SQL
Ch 4: SQL BASICS – 2
- DDL Variants in MSSQL
- DML Variants in MSSQL
- INSERT & INSERT INTO
- SELECT & SELECT INTO
- Basic Operators in SQL
- Special Operators in MSSQL
- ALTER, ADD, TRUNCATE, DROP
Ch 5: Data Imports, Schemas
- Data Imports with Excel
- ORDER BY & UNION
- UNION ALL For Sorting Data
- Creating, Using Schemas
- Real-world Banking Database
- Table Migrations @ Schemas
- 2 Part, 3 Part & 4 Part Naming
Ch 6 : Constraints, Index Basics
- Need for Constraints, Keys
- NULL, NOT NULL, UNIQUE
- Primary Key & Foreign Key
- RDBMS and ER Models
- Identity Property, Default
- Clustered Index, Primary Key
- Non Clustered Index, Unique
Ch 7: Joins & Views Basics
- JOINS: Purpose. Inner Joins
- Left / Right / Full Outer Joins
- Cross Joins, Query Tuning
- Creating & Using Views
- DML, SELECT with Views
- RLS : WITH CHECK OPTION
- System Views & Metadata
Ch 8: Functions(UDF), Data Types
- Using Functions in MSSQL
- Scalar Value Functions
- Inline & Multiline Functions
- Date & Time Functions
- String, Aggregate Functions
- Data Types : Integer, Char, Bit
- SQL Variant, Timestamp, Date
Ch 9: Stored Procedures,Models
- Stored Procedures & Usage
- Creating, Testing Procedures
- Encryption, Deferred Names
- SPs for Validations, Analysis
- System SPs, Recompilation
- Normal Forms & Types
- Data Models, Self-References
Ch 10: Triggers, Temp Tables
- Need for Triggers
- DDL & DML Triggers
- Using Memory Tables
- Data Replication, Automation
- Local & Global Temp Tables
- Testing & Using Temp Tables
- SELECT .. INTO & Bulk Loads
Ch 11: DB Architecture, Locks
- Planning VLDBs : Files, Sizing
- Filegroups, Extents & Types
- Log Files : VLF, Mini LSN
- Table Location, Performance
- Schemas, Transfer, Synonyms
- Transactions Types, Lock Hint
- Query Blocking Scenarios
Ch 12 : Cursors & CTEs, Links
- Cursors : Realtime Use
- Fetch & Access Cursor Rows
- CTEs for SELECT, DML
- CTEs: Scenarios & Tuning
- Linked Servers, Remote Joins
- Linked Servers: MSDTC, RPC
- Tuning Remote Queries
Ch 13: Merge, Upsert & Rank
- Need for Merge in ETL
- Incremental Loads with SQL
- MERGE and RANK Functions
- Window Functions, Partition
- Identify, Remove Duplicates
Ch 14: Grouping & Cube
- Group By & HAVING
- Cube, Rollup & Grouping
- Joins with Group By
- 3 Table, 4 Table Joins
- Query Execution Order
Ch 15: Self Joins, Excel Analysis
- Self Joins & Self References
- UNION, UNION ALL
- Sub Queries with Joins
- IIF, CASE, EXISTS Statements
- Excel Analytics, Pivot Reports
Module 2: Fabric Data Engineer
Ch 1: Fabric Introduction
- Need for Fabric, Big Data
- Fabric Data Engineering Model
- Fabric Components (Items)
- Microsoft Fabric: Advantages
- Cloud Warehouse Uses
- Benefits of Fabric Over Azure
- Azure Versus Fabric DWH
Ch 2: Fabric Account, Workspace
- Need for Fabric Workspace
- Workspace Creation Process
- Pins and New Items
- Item Categorization
- ETL, Storage, Analytical
- Streaming, Monitoring
- Compute & Separation
Ch 3: Fabric Architecture
- Intelligent Data Foundation
- Polaris Distributed Engine
- Stateless & Stateful
- Cache, Metadata, Xact & Data
- Fabric Tasks, Inputs & DAG
- State Machine & Statistics
- Hot Spot Recovery
Ch 4: Fabric Warehouse
- Fabric Warehouse Creation
- Fabric Warehouse Features
- Fabric Warehouse Properties
- Fabric Warehouse Limitations
- DWH Internal Operations
- Default Schemas & Objects
Ch 5: Fabric Data Types
- Realtime use of Fabric Houses
- Exact, Approximate Numbers
- Date and Time Data Types
- Fixed & Variable Length
- Binary & String Data Types
- Fabric Type Limitations
Ch 6: SSMS Connections
- Warehouse SQL Connection
- Database Engine Server
- Multi Factor Authentication
- Warehouse Artifacts
- Executing .SQL Scripts
- Testing Fabric Artifacts
Ch 7: Fabric Caching
- Fabric Caching Process
- In-memory Cache, Disk Cache
- Cache Types: LRU /MRU
- Cold Cache / Cold Run
- Realtime use of Caching
- Performance Advantages
- Warehouse Optimizations
Ch 8: Fabric Statistics
- Query Engine Options
- Statistics Types
- Leverage Statistics
- Auto, Manual Statistics
- Update Statistics
- Statistics Consistency
- Statistics Lists & Reports
Ch 9: Time Travel
- Continuous Data Protection
- Data Storage, Retention
- FOR TIMESTAMP AS OF
- Time Travel Scenarios
- Time Travel Implementation
- Time Travel on Queries
- Time Travel Limitations
Ch 10: Aggregated Data Store
- Options for Data Aggregations
- Save As table, Save As View
- Single Table Aggregations
- Multi Table Aggregations
- Dynamic Conditions
- Parameterized Aggregations
Ch 11: Zero Copy Cloning
- User Layer, Storage Layer
- Cloning & Parquet Files
- Synapse Data Warehouse
- Data History Retention
- Point In Time , Schema Level
- Zero Copy Cloning Limitations
Ch 12: Fabric Security
- Workspace Security
- Warehouse Security
- Item Security & Roles
- Adding AD Users
- Item Security Limitations
- MFA & Client Security
Ch 13: Fabric Data Factory
- ETL Implementation Options
- Need for Fabric Data Factory
- ETL Operations in FDF
- Data Sources, Transformations
- Data Destinations (Sinks)
- Creating Pipelines
Ch 14: Fabric Pipelines
- Activities and Connections
- Gateways & OnPrem Access
- Data Sets & Activity Sets
- Data Activator & Alerts
- Run ID & Monitoring
- Pipeline Creation, Verification
- Activity Check, Schedule
Ch 15: Fabric Pipelines Design
- Creation Options for Pipelines
- Azure SQL DB Data Loads
- Creating Data Sets
- RRR Transformations
- Copy Command Usage
- Internal Staging (Workspace)
- Data Loads to FDWH
Ch 16: Fabric Aggr Data Loads
- Aggregation Scenarios
- Creating Views in TSQL
- Using Views in FDF Pipelines
- Using Pipeline Editor
- Data Loads to Warehouse
- Pipeline Verifications
Ch 17: ETL Staging
- Staging : Advantages
- Caching & Storing Concept
- Staging Types in Fabric
- Workspace & External
- External Stages in Pipelines
- Compressions & Advantages
- Pipeline Trigger, Monitor
Ch 18: OnPrem Gateways
- Need for On_Premi Gateway
- Installing & Configuring
- Authentication, Usage
- OnPremises Connections
- Pipelines for Data Loads
- Warehouse Data Storage
- Data Refresh with Gateways
Ch 19: Fabric Lakehouse
- Need for Fabric Lakehouse
- Files and Tables Storage
- Data Sources: Parquet Files
- Transformation Options
- Direct Lake Concepts
- Lakehouse Consumption
- Lakehouse Real time Use
Ch 20: Lakehouse File Loads
- Creating Lakehouse
- Copy Data Wizard
- Azure SQL Database Source
- File Data Loads in Lakehouse
- Concurrency & Batch Count
- Pipeline Execution Tests
- Pipeline Monitor Check
Ch 21: Lakehouse Aggr Loads
- Aggregated Data Store
- Plan & Design Aggregations
- Testing Aggregations
- Pipelines for Data Compute
- Data Copy Options
- Pipeline Optimizations
- Data Loads and Verification
- Pipeline Execution Tests
- Pipeline Monitor Check
Ch 22: MultiTable Loads in LH
- Table Loads Connections
- Data Load in Lakehouse
- Using Copy Data Wizard
- Data Store in Lakehouse
- View Run History, Executions
- SQL End Points & Access
- Lakehouse Schemas
Ch 23: Lakehouse Visual Queries
- Visual Query Interface
- Visual Editor & Tables / Views
- Merge, Remove, Sort Tfns
- Data Preview, Save As Table
- Save As View : Advantages
- Using Schemas, Identifiers
- TDS Packets & Transfer Units
Ch 24: File Explorer
- Installing One Lake Explorer
- Autocreation of Folders
- Workspace Directories
- Warehouse Directories, Logs
- Lakehouse Folders, Files
- Lakehouse Uploads
- Explorer Tool Limitations
Ch 25: Power Query Level 1
- Power Query Concept
- Need for Power Query
- Data Flow Gen 1
- Data Flow Gen 2
- Power Query Items
- Differences with Copy Activity
- ETL, ELT Process
Ch 26: Power Query Level 2
- Data Flow Gen2 Operations
- PQ Online Editor
- Working with Binary Content
- Detailed Data Options
- Data Cleansing Options
- Step Names, Aggregations
- Warehouse Data Loads
Ch 27: Power Query Level 3
- Binding Power Query Steps
- Edit / Delete Steps
- Optimizing Power Query
- ETL & ELT with Power Query
- Advanced Editor
- M Language Expressions
- Duplicate / Reference Queries
Ch 28: Fabric Notebooks
- Need for Notebooks
- Fabric Notebook Types
- Get / Prep / Analyze
- Sessions, Markdown Folding
- Standard, High Concurrency
- Magic Command
- Freeze Cells
Ch 29: Spark SQL Notebooks
- Creating Environment
- Creating Spark Clusters
- Spark Cluster Compute
- SQL Analytics in Notebooks
- Visual Query Vs SQL
- Cell Execution Options
- Magic Command Usage
Ch30: PySpark Notebooks
- Creating / Using Environment
- PySpark Notebook Sessions
- Reading Source Data
- Data Prep & Aggregations
- Data Loads, Analytics
- Cell Execution Options
- Markdown Cells
Ch 31: StreamHouse, KQL
- Need for Stream House
- Auto creation of KQL
- Manual KQL Databases
- Verification & Usage
- Differences with Warehouse
- Differences with Lakehouse
Ch 32: KQL Query Sets
- KQL Database ExtractionFile Imports – on Premises
- Metadata Edit Options
- Query Analytics
- Exports, Visualizations
- Query Sets Versus Notebooks
Ch 33: Fabric Data Activator
- Need for Alerts, Notifications
- Fabric Data Activator Options
- Alert Conditions, Thresholds
- Email Notifications
- Events & Notifications
- Edit / Enable / Disable
Ch 34: Model Layouts
- Need for Layouts
- Creating Model Layouts
- Adding Refences, Keys
- Power BI Semantic Models
- Creating Report Items
- Using Power BI Desktop
Ch 35: Azure Synapse Migrations
- Azure Synapse DWH
- Azure Synapse Connections
- Migrating to Fabric
- Compatibility Checks
- Synapse Vs Fabric Warehouse
- Fabric DWH Advantages
Ch 36: DP 700 Exam Guidance
End to End Realtime Project: Ecommerce Domain
Module 3: Power BI
Ch 1 : Power BI Introduction
- Reporting Basics & Types
- Interactive,Analytical Reports
- Paginated Reports (RDL)
- Power BI Eco System
- Power BI Tools,Service,Server
- Need for Power Query (M)
- Need for DAX & Cloud
Ch 2: Power BI Basic Reports
- Power BI Desktop Installation
- Basic Report Design (PBIX)
- Data View, Data Models
- Data Points, Aggregations
- Focus Mode, Spotlight, Exports
- ToolTip, PBIX and PBIT
- Visual Interactions & Edits
Ch 3 : Grouping, Hierarchies
- Creating Groups in Power BI
- Groups : Creation & Usage
- Group Edits Options
- Bins & Bin Size, Bin Count
- Hierarchies: Creation, Use
- Drill Down, Drill Up
- Conditional Drill Down
Ch 4 : Visual Sync, Filters
- Slicer & Single Select
- Multi Select Options
- Integer, Character Slicers
- Visual Sync with Slicers
- Filters: Visual, Page, Report
- Drill Thru Filters & Usage
- Basic, Top & Advanced
- Clear Filter Options, Resets
Ch 5 : Bookmarks, Big Data
- Bookmarks Creation & Usage
- Visual Interactions, Bookmarks
- Images : Actions, Bookmarks
- Big Data Access with Power BI
- Storage Modes: Direct Query
- Import & Performance Impact
- Formatting & Data Refresh
- Summary, Date Time Formats
Ch 6 : Power BI Visualizations
- Chart and Bar Visuals
- Line and Area Charts
- Maps, TreeMaps, HeatMaps
- Funnel, Card, Multrow Card
- PieCharts & Settings
- Waterfall, Sentiment Colors
- Scatter Chart, Play Axis
- Infographics, Classifications
Ch 7 : Power Query Level 1
- Power Query (Mashup)
- ETL Transformations in PBI
- Power Query Expressions
- Table Combine Options
- Merge, Union All Options
- Table Transformations
Ch 8 : POWER QUERY LEVEL 2
- Any Column Transformations
- String / Text Transformations
- Numeric Analytics & Mashup
- Date Time Transformations
- Add Column Transformations
- Expressions and New Columns
Ch 9 : POWER QUERY LEVEL 3
- Parameters in Power Query
- Static Parameters, Defaults
- Dynamic Dropdowns, Lists
- Linking with Table Queries
- Column From Examples
- Step Edits, Type Conversions
Ch 10 : Power BI Cloud – 1
- Power BI Cloud Concepts
- Workspace Creation, Usag
- Report Publish & Edits
- Semantic Models in Realtime
- Dashboard Creation, Usage
- Clone, Share, Subscribe
- Q&A, Lineage, Settings
Ch 11 : Power BI Cloud – 2
- Data Gateways, Data Refresh
- Data Source Configurations
- Data Refresh & Scheduling
- Gateway Optimizations
- Semantic Model Optimizations
- Report Optimizations
- Dashboard Optimizations
Ch 12 : Power BI Cloud – 3
- Power BI Apps, Shares
- App Sections & Options
- App Updates, Security
- Excel Analytics
- Data Explorer Option
- Sharing, Subscriptions
- Alerts, Metrics, Insights
Ch 13 : Report Server & DAX
- Power BI Report Server
- Report Database, TempDB
- Web Service & Server URL
- Paginated Reports (RDL)
- Report Builder Tool Usage
- DAX : Purpose, Realtime Use
Ch 14: DAX Level 2
- DAX Measures Creation, Use
- DAX Functions: IIF, ISBLANK
- SUM, CALCULATE Functions
- DAX Cheat Sheet : Examples
- Quick Measures in Power BI
- Running Totals, Filters
Ch 15 : DAX Level 3
- Star Rating Calculations
- Data Models & DAX
- Star & Snowflake Schemas
- Dimensions, Fact Tables
- DAX Expressions & Joins
- DAX Variables, Usage
Ch 16 : DAX Level 4
- Dynamic Report with DAX
- SELECTED MEMEBER
- Time Intelligence with DAX
- PARALLELPERIOD, DATE
- DAX with Big Data
- Big Data Analytics
Ch 17 : Realtime Project Phase 1
- Project Requirement Spec
- Understanding Data, Formats
- Report Pattern Design
- Report Design & Modelling
- Power Query, DAX, Insights
- Analytical Reports in Cloud
Ch 18 : Realtime Project Phase 2
- Complete Project Solution
- Project FAQs, Key Roles
- Real-world Considerations
- Power BI Admin Concepts
- Resume Points, FAQs
- PL 300 Exam Guidance
