No. All topics—from SQL basics to Power BI and Fabric—are taught from scratch with step-by-step guidance.
Fabric Data Analyst is a promising job role that deals with Data, Analysis, Derived Information and drive to Infographics of enterprise content. This role also involves Data collection, data processing, and data analysis to identify trends, patterns, and relationships that can be used to solve problems and make informed decisions with ease!
✅ Power BI with Fabric
✅ Fabric DWH with Power BI
✅ Fabric Lakehouse with Power BI
✅ Fabric Stream House & Power BI
✅ Dynamic Row-Level Security
✅ Data Activator, Alerts
✅ Big Data Analytics
✅ DP 600 Exam Guidance
✅ Real Time Project
✅ 1:1 Mentorship, Resume
Module 1: SQL Server TSQL (MS SQL) Queries
Ch 1: Data Engineer Job Roles
- Introduction to Data
- Data Engineer Job Roles
- Data Engineer Challenges
- Data and Databases Intro
Ch 2: Database Intro & Installations
- Database Types (OLTP, DWH, ..)
- DBMS: Basics
- SQL Server 2025 Installations
- SSMS Tool Installation
- Server Connections, Authentications
Ch 3: SQL Basics V1 (Commands)
- Creating Databases (GUI)
- Creating Tables, Columns (GUI)
- SQL Basics (DDL, DML, etc..)
- Creating Databases, Tables
- Data Inserts (GUI, SQL)
- Basic SELECT Queries
Ch 4: SQL Basics V2 (Commands, Operators)
- DDL: Create, Alter, Drop, Add, modify, etc..
- DML: Insert, Update, Delete, select into, etc..
- DQL: Fetch, Insert… Select, etc..
- SQL Operations: LIKE, BETWEEN, IN, etc..
- Special Operators
Ch 5: Data Types
- Integer Data Types
- Character, MAX Data Types
- Decimal & Money Data Types
- Boolean & Binary Data Types
- Date and Time Data Types
- SQL_Variant Type, Variables
Ch 6: Excel Data Imports
- Data Imports with Excel
- SQL Native Client
- Order By: Asc, Desc
- Order By with WHERE
- TOP & OFFSET
- UNION, UNION ALL
Ch 7: Schemas & Batches
- Schemas: Creation, Usage
- Schemas & Table Grouping
- Real-world Banking Database
- 2 Part, 3 Part & 4 Part Naming
- Batch Concept & “Go” Command
Ch 8: Constraints, Keys & RDBMS – Level 1
- Null, Not Null Constraints
- Unique Key Constraint
- Primary Key Constraint
- Foreign Key & References
- Default Constraint & Usage
- DB Diagrams & ER Models
Ch 9: Normal Forms & RDBMS – Level 2
- Normal Forms: 1 NF, 2 NF
- 3 NF, BCNF and 4 NF
- Adding Keys to Tables
- Cascading Keys
- Self Referencing Keys
- Database Diagrams
Ch 10: Joins & Queries
- Joins: Table Comparisons
- Inner Joins & Matching Data
- Outer Joins: LEFT, RIGHT
- Full Outer Joins & Aliases
- Cross Join & Table Combination
- Joining more than 2 tables
Ch 11: Views & RLS
- Views: Realtime Usage
- Storing SELECT in Views
- DML, SELECT with Views
- RLS: Row Level Security
- WITH CHECK OPTION
- Important System Views
Ch 12: Stored Procedures
- Stored Procedures: Realtime Use
- Parameters Concept with SPs
- Procedures with SELECT
- System Stored Procedures
- Metadata Access with SPs
- SP Recompilations
Ch 13: User Defined Functions
- Using Functions in MSSQL
- Scalar Functions in Real-world
- Inline & Multiline Functions
- Parameterized Queries
- Date & Time Functions
- String Functions & Queries
- Aggregated Functions & Usage
Ch 14: Triggers & Automations
- Need for Triggers in Real-world
- DDL & DML Triggers
- For / After Triggers
- Instead Of Triggers
- Memory Tables with Triggers
- Disabling DMLs & Triggers
Ch 15: Transactions & ACID
- Transaction Concepts in OLTP
- Auto Commit Transaction
- Explicit Transactions
- COMMIT, ROLLBACK
- Checkpoint & Logging
- Lock Hints & Query Blocking
- READPAST, LOCKHINT
Ch 16: CTEs & Tuning
- Common Table Expression
- Creating and Using CTEs
- CTEs, In-Memory Processing
- Using CTEs for DML Operations
- Using CTEs for Tuning
- CTEs: Duplicate Row Deletion
Ch 17: Indexes Basics, Tuning
- Indexes & Tuning
- Clustered Index, Primary Key
- Non Clustered Index & Unique
- Creating Indexes Manually
- Composite Keys, Query Optimizer
- Composite Indexes & Usage
Ch 18: Group By Queries
- Group By, Distinct Keywords
- GROUP BY, HAVING
- Cube( ) and Rollup( )
- Sub Totals & Grand Totals
- Grouping( ) & Usage
- Group By with UNION
- Group By with UNION ALL
Ch 19: Joins with Group By
- Joins with Group By
- 3 Table, 4 Table Joins
- Join Queries with Aliases
- Join Queries & WHERE, Group By
- Joins with Sub Queries
- Query Execution Order
Ch 20: Sub Queries
- Sub Queries Concept
- Sub Queries & Aggregations
- Joins with Sub Queries
- Sub Queries with Aliases
- Sub Queries, Joins, Where
- Correlated Queries
Ch 21: Cursors & Fetch
- Cursors: Realtime Usage
- Local & Global Cursors
- Scroll & Forward Only Cursors
- Static & Dynamic Cursors
- Fetch, Absolute Cursors
Ch 22: Window Functions, CASE
- IIF Function and Usage
- CASE Statement Usage
- Window Functions (Rank)
- Row_Number( )
- Rank( ), DenseRank( )
- Partition By & Order By
Ch 23: Merge(Upsert) & CASE, IIF
- Merge Statement
- Upsert Operations with Merge
- Matched and Not Matched
- IIF & CASE Statements
- Merge Statement inside SPs
- Merge with OLTP & DWH
Ch 24: Key Take-Aways from Module 1
- Case Study 1: Medicare Scenario
- Case Study 2: Ecommerce Scenario
Module 2: Power BI with AI, CoPilot
Ch 1: Power BI Intro, Installation
- Power BI & Data Analysis
- 5 Design Tools, 3 Techniques
- 2 Hosting Solutions
- Power BI with Co-Pilot & AI
- Power BI Installation
Ch 2: Report Design Concepts
- Basic Report Design (PBIX)
- Get Data, Canvas (Design)
- Data View, Data Models
- Data Points, Spotlight
- Focus Mode, PDF Exports
Ch 3: Visual Interactions, PBIT
- Visual Interactions & Edits
- Limitations with Visual Edits
- Creating Power BI Templates
- CSV Exports & PBIT Imports
Ch 4: Grouping, Hierarchies
- Creating Groups : Lists
- Creating Groups: Bins
- List Items & Group Edits
- Bin Size & Bin Count
Ch 5: Slicer & Visual Sync
- Slicer Visual in Power BI
- Slicer: Format Options
- Single Select, Multi Select
- Slicer: Select All On / Off
- Visual Sync with Slicers
Ch 6: Hierarchies & Drill-Down
- Hierarchies: Creation, Use
- Hierarchies: Advantages
- Drill Up, Drill Down
- Conditional Drill Down
- Filtered Drill Down, Table View
Ch 7: Filters & Drill Thru
- Power BI Filters
- Basic, Top & Advanced
- Visual Filters, Page Filters
- Report Level Filters, Clear Filter
- Drill Thru Filters & Usage
Ch 8: Bookmarks, Buttons
- Power BI Bookmarks
- Images: Actions, Bookmarks
- Buttons: Actions, Bookmarks
- Page to Page NavigationsScore Cards, Master Pages
Ch 9: SQL DB Access & Big Data
- SQL DB Access, Queries
- Storage Modes: Direct Query
- Formatting & Date Time
- Storage Modes in Power BI
- Azure (Big Data) Access & Formatting
Ch 10: Power BI Visualizations
- Charts, Bars, Lines, Area
- TreeMaps & HeatMaps
- Funnel, Card, Multrow Card
- PieCharts & Waterfall
- Scatter Chart, Play Axis
- Infographics, Classifications
Ch 11: Power Query Introduction
- Power Query (Mashup)
- ETL Transformations in PBI
- Power Query Expressions
- Table Combine Options
- Merge, Union All Options
- Close, Apply & Visualize
Ch 12: Power Query : Table Tfns
- Table Duplicate, Header Promotion
- Group By Transformation
- Aggregate, Pivot Operation
- Reverse Rows, Count Rows
- Advanced Power Query Mode
Ch 13: Power Query: Column Tfn
- Any Column Transformations
- Data Type Detection, Change
- Rename, Replace, Move
- Fill Up, Fil Down
- Step Edits & Rollbacks
Ch 14: Power Query: Text, Date
- String / Text Transformations
- Split, Merge, Extract, Format
- Numeric and Date Time
- Add Column & Expressions
- Expressions and New Columns
- Column From Examples
Ch 15: Power Query: Parameters
- Parameters in Power Query
- Static Parameters, Defaults
- Dynamic Dropdowns, Lists
- Linking with Table Queries
- Step Edits, Type Conversions
Ch 16: Power BI Cloud: Publish
- Power BI Cloud Concepts
- Workspace Creation, Usage
- Report Publish Cloud
- Report Edits in Cloud
- Semantic Models & Usage
Ch 17: Power BI Cloud Dashboards
- Power BI Dashboards
- Dashboard Creation, Usage
- Pin Visuals, Pin LIVE Pages
- Add Image, Video Tiles
- Q&A & Pin Tiles
Ch 18: Power BI Cloud Operations
- Report Shares, Alerts
- Subscriptions, Exploration
- Downloads & Edits
- Report Cloning in Cloud
- QR Codes, Web Publish
- Lineage & Metrics
Ch 19: Power BI Cloud Gateways
- Data Gateways, Data Refresh
- Install, Configure Gateways
- Data Sources Configurations
- Data Refresh & Scheduling
- Gateway Optimizations
Ch 20: Power BI Cloud Apps
- Power BI Apps: Creation
- App Sections & Content
- Audience Options
- App Security & Sharing
- App Updates, Favourites
- App URL, End User Access
Ch 21: Power BI Report Server
- SQL Server 2025 (Mandatory Installations)
- Power BI Report Server
- Report Server Vs Cloud
- Installation, Configuration
- RS Config Tool Options
- Report Database, TempDB
- Web Service & Server URL
Ch 22: Paginated Reports
- Report Builder Tool
- Paginated Report (RDL)
- Report Expressions (RDL)
- Tablix, Chart Wizards
- Fields & Drill-Down
- RDL Report Publish
Ch 23: DAX Concepts (Basics)
- DAX Concepts: Intro & Realtime Need
- DAX Columns: Creation, Use
- DAX Measures: Creation, Use
- DAX Functions: IIF, ISBLANK
- SUM, CALCULATE Functions
- DAX Cheat Sheet
Ch 24: DAX Quick Measures
- Quick Measures in Power BI
- Average & Filters
- Running Totals
- Star Rating Calculations
- DAX Measures in Data View
- DAX in Visuals
- DAX in Cloud Reports
Ch 25: Data Modelling, DAX
- Dimensions Tables
- Fact Tables & DAX Measures
- Data Models & Relations
- DAX Expressions
- Star & Snowflake Schemas
- DAX Joins & Expressions
Ch 26: DAX Joins, Variables
- CALCULATEX & Variables
- COUNT, COUNTA, etc..
- SUM, SUMX, etc..
- SELECTED MEMEBER
- Filter Context, RETRUN
- Dynamic Report with DAX
Ch 27: DAX Time Intelligence
- Need for Time Intelligence
- Date Table Generation
- Time Intelligence with DAX
- PARALLELPERIOD, DATE
- CALENDAR, Total Functions
- YTD, QTD, MTD with DAX
Ch 28: DAX – Row Level Security
- RLS: Row Level Security
- Data Modelling & Roles
- Verify Roles (Testing)
- Add Cloud Users to Roles
- Dynamic Row Level Security
- Testing RLS in Power BI
Ch 29: Analytical Reports
- Analytical Report Concepts
- Excel Data Analytics
- Excel with Power BI Cloud
- SQL, AVRO, JSON Sources
- Analyse in Excel (Cloud)
- Excel Reports to Cloud
Ch 30: PL 300 Exam Guidance, CoPilot
- PL 300 Exam (Microsoft Certified Data Analyst) Guidance
- PL 300 Exam Mocks
- AI Components in Power BI
- CoPilot Practical Uses
- CoPilot with Desktop
- CoPilot with Cloud
- Need for AI Analytics (Fabric)
Ch 31: Key Take-Aways from Module 2
- Case Study 1: Medicare: Tasks, Solutions
- Case Study 2: ECommerce: Task, Solutions
- Chapter Wise Assignments: Solutions
- Dailly Assignments: Review (Feedback)
- Weekly Mock Interview: Feedbacks
Module 3: Python (For Data Analysts)
Ch 1: Python Introduction
- Python Introduction
- Python Versions
- Python Implementations
- Python Installations
- Python IDE & Usage
- Jupyter Notebooks
Ch 2: Python Operations
- Basic Operations in Python
- Python Scripts, Print()
- Single, Multiline Statements
- Python: Internal Architecture
- Compiler Versus Interpreter
Ch 3: Data Types & Variables
- Integer / Int Data Types
- Float, String Data Types
- Sequence Types: List, Tuple
- Range, Complex & memview
- Retrieving Data Type: type()
Ch 4: Python Operators
- Arithmetic, Assignment Ops
- Comparison Operators
- Operator Precedence
- If … Else Statement, Pass
- Short Hand If, OR, AND
- ELIF and ELSE IF Statements
Ch 5: Python Loops, Iterations
- Python Loop & Realtime Use
- Python While Loop Statement
- Break and Continue Statement
- Iterations & Conditions
- Exit Conditions & For Loops
- iter() and Looping Options
Ch 6: Python Functions
- Python Functions & Usage
- Function Parameters
- Default & List Parameters
- Python Lambda Functions
- Recursive Functions, Usage
- Return & Print @ Lamdba
Ch 7: Python Modules
- Import Python Modules
- Built In Modules & dir
- datetime module in Python
- Date Objections Creation
- strftime Method & Usage
- imports & datetime.now()
Ch 8: Python User Inputs & TRY
- Try Except, Exception Handling
- Raise an exception method
- TypeError, Scripting in Python
- Python User Inputs
- Python Index Numbers
- input() & raw_input()
Ch 9: Python File Handling
- File Handling, Activities
- Loop, Write, Close Files
- Appending, Overwriting
- import os, path.exists
- f.open, f.write
- f.read, f.close
Ch 10: Pandas DataFrames 1
- Installation of Pandas
- Python Modules & Pandas
- Pandas Codebase & Usage
- import pandas.DataFrame
- Pandas Series, arrays
Ch 11: Pandas DataFrames 2
- Indexes & Named Options
- Locate Row and Load Rows
- Row Index & Index Lists
- Load Files Into a DataFrame
- df.to_string() Function
- tail() & null() Function
Ch 12: Pandas Transformations
- Pandas – Cleaning Data
- Replace, Transform Columns
- Data Discovery & Column Fill
- Identify & Remove Duplicates
- dropna(), fillna() Functions
- Data Plotting & matlib Lib
Ch 13: Realtime Project (Banking / Finance) For Data Analysis [End to End]
Module 4: Fabric (For Data Analysts)
👉 Fabric Warehouse
👉 Fabric Lakehouse
👉 Fabric Semantic Models
👉 Fabric Stream House
👉 Fabric with Power BI
👉 End to End Integrations
👉 DP 600 Exam Guidance
👉 DP 600 Exam Samples
What is Fabric Data Analyst Job Role?
This program trains you in SQL Server TSQL, Power BI with Fabric, Python for Analytics, and Microsoft Fabric components such as Warehouse, Lakehouse, Semantic Models, and Stream House. It includes 100% hands-on practice and DP-600 exam guidance.
Who should join this Fabric Data Analyst training?
Freshers, non-IT learners, Power BI users, SQL developers, Business Analysts, and anyone who wants to move into Azure analytics, Power BI + Fabric workflows, or enterprise data modelling.
What modules are included in the course?
Module 1: MSSQL & TSQL – 3 Weeks, 1 Mini Project
Module 2: Power BI with Fabric – 4 Weeks, 1 Realtime Project
Module 3: Python – 3 Weeks, 1 Mini Project
Module 4: Fabric Analytics + DP-600 Exam Guidance
What SQL skills will I learn?
You learn database fundamentals, commands, joins, keys, normalization, views, stored procedures, functions, triggers, transactions, indexes, grouping, CTEs, window functions, merge (upsert), and two case studies.
What Power BI skills are included?
Report design, filters, visual interactions, groups, slicers, drill-down, bookmarks, buttons, templates, big data access, cloud publishing, dashboards, gateways, apps, Report Server, and paginated reports.
What DAX topics are covered in the course?
DAX basics, columns, measures, functions, quick measures, variables, joins, context, star/snowflake schema modelling, time intelligence (YTD/QTD/MTD), and Row Level Security (RLS).
Is Power Query included?
Yes. Table transformations, column transformations, text/date operations, merge, pivot, grouping, parameters, dynamic lists, and step edits are covered in detail.
Does this training cover Power BI Cloud & Report Server?
Yes. You will learn cloud publishing, semantic models, dashboard creation, alerts, subscriptions, lineage, metrics, publishing RDL reports, and Report Server configuration.
Does the course include Python for Data Analysts?
Yes. Python basics, loops, functions, file handling, Pandas, DataFrames, cleaning, transformations, duplicates, plotting, and a complete real-time Banking/Finance analytics project are included.
What Fabric components will I learn?
Fabric Warehouse, Fabric Lakehouse, Fabric Semantic Models, Fabric Stream House, and real-time end-to-end Fabric integrations with Power BI.
Is this course helpful for PL-300 or DP-600 certification?
Yes. PL-300 fundamentals are covered through Power BI training, and the course provides dedicated DP-600 exam preparation, samples, and guidance.
Are there real-time projects in this course?
Yes. SQL case studies, Power BI real-time projects, Python analytics projects, and Fabric analytics workflows are included with tasks and solutions.
Do you provide daily assignments and weekly mocks?
Yes. Daily assignments, chapter-wise exercises, weekly mock interviews, and feedback sessions are part of the program.
Is this Fabric Analyst course suitable for beginners?
Absolutely. The syllabus is structured from basic concepts to advanced analytics, making it beginner-friendly and suitable for non-technical learners.
What job roles can I apply for after completion?
Fabric Data Analyst, Power BI Developer, BI Analyst, SQL Analyst, Data Visualization Engineer, Reporting Analyst, Python Analyst, and Azure BI Analyst.
Do you teach AI/Copilot in Power BI?
Yes. AI capabilities, Copilot features in Desktop and Cloud, AI-assisted report building, and Fabric AI analytics are covered.
Does the course include data modelling?
Yes. You will learn Fact & Dimension tables, star and snowflake schemas, relationships, DAX joins, semantic modelling, and cloud-based data modelling.
What training modes are available?
Live Online Training, Self-Paced Videos, Corporate Training, and Free Demos with the trainer. Contact numbers are clearly mentioned in the course file for support.
Placement Partners
SQL SCHOOL
24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.
Why Choose SQL School
- 100% Real-Time and Practical
- ISO 9001:2008 Certified
- Weekly Mock Interviews
- 24/7 LIVE Server Access
- Realtime Project FAQs
- Course Completion Certificate
- Placement Assistance
- Job Support
