Ch 1: SQL Database Job Roles

• Database Intro
• OLTP, DWH, OLAP
• DBMS Basics
• Data Engineer Job Roles

Ch 2: Database Intro & Installations

• SQL Server Installations
• Instance & Collations
• SSMS Tool Installation
• Connections, Authentications

Ch 3: SQL Basics V1 (Commands)

• 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
• DML: Insert, Update, Delete
• DQL: Select, Fetch
• Add, Truncate Statements
• SQL Operators

Ch 5: Data Types & Variables

• Integer Data Types
• Character, MAX Data Types
• Decimal & Boolean Data Types
• Date and Time Data Types
• SQL_Variant Type

Ch 6: Data Imports

• Data Imports with Excel
• Data Imports with CSV
• Data Types Detection
• OLE-DB Connections
• ORDER BY, TOP, OFFSET

Ch 7: Schemas & Batches

• Schemas & Table Grouping
• Real-world Banking Database
• 2 Part, 3 Part & 4 Part Naming
• Batch Concept & “Go” Command

Ch 8: Constraints, Keys & RDBMS

• Null, Not Null Constraints
• Unique Key & Check
• Primary Key Constraint
• Foreign Keys, Default
• DB Diagrams & ER Models

Ch 9: Normal Forms & RDBMS

• Normal Forms: 1 NF, 2 NF
• 3 NF, BCNF and 4 NF
• 1:1, 1:M, M:1 Cardinality
• Cascading Keys, Self Referencing Keys

Ch 10: Joins & Queries

• Joins: Table Comparisons
• Inner Joins & Matching Data
• Outer Joins: LEFT, RIGHT
• Full Outer Joins & Aliases
• Self Joins & Aliases

Ch 11: Sub Queries

• Basic Sub Queries
• Aggregations
• Combining Queries
• Correlated Sub Queries
• UNION, UNION ALL

Ch 12: Group By Queries

• Group By, Distinct
• GROUP BY, HAVING
• Cube( ) and Rollup( )
• Sub Totals & Grand Totals
• Grouping( ) & Usage
• ISNULL, COALESCE

Ch 13: Joins with Group By, Sub Queries

• 3 Table, 4 Table Joins
• Join Queries & WHERE
• Join & Group By, Sub Queries
• IIF(), CASE Statement
• EXISTS, NOT EXISTS
• Query Execution Order

Ch 14: Views & RLS

• Views: Realtime Usage
• DML, SELECT with Views
• WITH CHECK OPTION
• Row Level Security (RLS)
• Important System Views

Ch 15: Functions & Queries

• User Defined Functions
• Scalar, Table Value Functions
• Variables & Parameters
• Date & Time Functions
• String Functions
• Aggregated Functions
• Data Conversion Functions

Ch 16: Advanced SQL & Window Functions

• Window Functions (Rank)
• Row_Number, DenseRank
• Partition By & Order By
• Lag & Lead Functions
• Pivot, UnPivot
• Running Totals
• Moving Average

Ch 17: Stored Procedures – 1

• Stored Procedures: Realtime Use
• Parameters Concept with SPs
• Procedures with SELECT
• System Stored Procedures
•  Stored Procedures, Tuning

Ch 18: Stored Procedures – 2

•  Merge Statement (Upsert)
• Merge with OLTP & DWH
• Matched and Not Matched
•  Merge & SP Recompilations

Ch 19: Triggers & Automations

• Need for Triggers in Real-world
• DDL & DML Triggers
• For / After Triggers
• Instead Of Triggers
• Disabling DMLs Triggers

Ch 20: Transactions & ACID

• Auto Commit Transaction
• Explicit Transactions
• COMMIT, ROLLBACK
• Checkpoint & Query Blocking
• READPAST, LOCKHINT
• TRY…CATCH & Error Handling

Ch 21: SQL Query Performance & Indexing

• Clustered vs Nonclustered Indexes
• Index Seek vs Scan
•  Execution Plans
• SARGable Queries
• Tuning Queries
• Avoiding SELECT *
• Indexing JOIN/WHERE columns
• Statistics Basics
• Query Optimization Examples

Ch 22: CTEs & Tuning

• Common Table Expression
• CTEs for Data Retrieval
•  CTEs for DML Operations
• Data Cleansing Techniques
• Duplicate Detection/Removal

Ch 23: Temp Tables & Query Techniques

•  Local & Global Temp Tables
• SELECT..INTO Statement
• Cursor Basics – When to Use & Avoid
• NULLIF
• Basic Execution-Plan Reading

Ch 24: Bonus / Advanced Module: SQL Server Internals

• Database Engine Components
• Parser, Compiler & Optimizer
• Parsing and Compilation
• Memory Manager & IO Managers

Real-Time Project on HealthCare Domain
Project Requirement:

Solve 20+ Real-World Healthcare Business Requirements.
Project Workflow:

Database Design → SQL Development → Data Analysis → Performance Optimization

Project Operational Flow:
Healthcare DB → Patients → Doctors → Appointments → Treatments → Billing → Insurance → SQL
Analysis → Stored Procedures → Performance Tuning → Business Reports

Business Requirements:
Monthly Hospital Revenue, Top Doctors By Patients Treated, Repeat Patients, Department
Performance, Average Treatment Cost, Unpaid Bills, Insurance Claim Analysis, Patient Trends,
Month-Over-Month Revenue And Top Procedures…

Section 1: Azure Data Factory & Synapse, ADLS
Ch 1: Azure Fundamentals

• Cloud Introduction, Azure
• Cloud Implementations
• Azure Account, Subscription
• Azure ETL & DWH Resources
• Azure Storage, IoT Resources

Ch 2: Azure Storage & ADLS

• Azure Data Lake Storage
• Azure BLOB Containers
• Access Keys
• SAS Keys
• IAM & ACLs

Ch 3: Azure Deployments, Azure SQL

• Azure SQL Server Deployment
• Azure SQL DB Deployment
• Azure SQL Database (OLTP)
• Azure Firewall Rules
• Connections from SSMS Tool

Ch 4: Azure SQL DB Migrations

• Azure Storage Account
• On-Premise SQL DB, bacpac
• Azure SQL DB Migration
• SQL Server Imports from BLOB
• Migration Verifications

Ch 5: Azure Synapse Analytics (DWH)

• Synapse Pool Architecture
• Control Node, Compute Node
• DMS (Data Movement Service)
• Azure DWH Tables: Partitions
• Distributions & MAXDOP

Ch 6: Azure Data Factory – Pipelines

• ADF Intro & Pipeline Artifacts
• Integration Runtime (IR)
• Linked Services, Datasets
• Copy Data Activity
• Azure SQL DB Loads
• Azure Synapse Analytics Writes
• Pipeline Validation, Runs

Ch 7: ADF: Azure Blob Data Loads

• ADF Author & Pipeline Runs
• Azure BLOB Storage Access
• Storage Containers in ADF
• Pipeline Staging
• Pipeline Logging
• Validations & Schedules

Ch 8: Table Incremental Loads

• Implement SCD with ADF
• Self Hosted IR: Realtime Use
• On-premise Data: Incr Loads
• Copy Method: Upsert, Keys
• Staging & ADF Optimizations
• Pipeline Logging

Ch 9: ADF Data Flow – 1

• Creating Data Flow Items
• Using Multiple Sinks
• Conditional Split Transformation
• Select, Sort, Union, Loops
•  ADF Debug Options

Ch 10: ADF Data Flow – 2

• Working with Multiple Tables
• Join Transform, Broadcast
• Surrogate Keys, Derived Cols
• ETL Loads Dates, Sink Options
• Aggregated Data Loads

Ch 11: ADF Data Flow – 3

• Pivot Transformation
• Group By & Pivot Keys
• Column Pattern, Deduplicate
• Lookup, Cached Lookup
• Tuing Transformations
• Tuning Data Flow, Spark

Ch 12: ADF Data Flow – 4

• Get Metadata
• IF & Lookup Transformation
• Cache Lookup
• Broadcast Options
• DIU, DOCP

Ch 13: ADF Parameters, Security

• Linked Service Parameters
• Creating Logins & Users
• Schemas, ETL Permissions
• Logins Parameters in ADF
• Dynamic Linked Services

Ch 14: SCD & ETL with Control Tables

• ADF Templates in Realtime
• Incremental Loads (SCD)
• Control Tables, Watermarks
• Lookup Activity, Delta Queries
•  SP Activity & Parameters
• Pipeline Parameters, SPs

Ch 15: ADF Metrics, Alerts

• Azure Insights
• Azure Metrics for ADF
• Azure Metrics for Synapse
• Alerts and Notifications
• Action Groups, Tuning Options

Ch 16: ADF with DevOps & CI/CD

• Git repositories and branching
• ADF Git integration
• Development / Test / Production environments
• Parameterized deployments
• Production release workflow

Ch 17: Azure Databricks

• Azure Databricks Deployments
• Azure Databricks Regions
• Classic Deployments
•  Access connector for Databricks

Ch 18: Azure Databricks with ADLS

• Creating IAM Users
• ADLS Security for Databricks
• Creating Service Principals
• Enterprise Applications
• Client ID, Secret ID
• External Tables (Delta)

Ch 19: Azure Stream Analytics

• Azure IoT Hubs
• Azure Stream Analytics
• LIVE Data Ingestions
• SAQL Queries
• Stream Analytics Jobs
•  Handling JSON Data

Ch 20: Azure Key Vaults

• Azure Key Vaults
• Azure Keys & Secrets
• Access Policies
• Secret Management
• Managed Identity

Ch 21: Azure Logic Apps

• Azure Logic Apps
• Logic Apps & Automations
• Azure Events
• Azure Triggers & Signals
• ADLS with Logic Apps

Section 2: Real-Time Projects for Data Factory
Real-Time Project: Online Travel Data Engineering Platform

Project Objective:
Build an end-to-end Azure Data Engineering solution to process, transform, and analyze Online Travel
business data from multiple sources.

Skills Gained:

• Data Ingestion & ETL Development
• Azure Data Factory Pipelines
• Data Orchestration (End to End)
• Data Lake Architecture, RBAC
• Real-Time Industry Experience
• Azure IoT, Stream Analytics
• Azure Databricks with Data Factory
• Components For Project
• ADF Pipelines
• Databricks Notebooks
• Synapse Analytics
• Apache Spark Schemas
• Monitoring & Alerts
• CI/CD Deployment
•  End to End Integrations
• IAM & Managed Identity

• End-to-End Real-Time Projects & Solutions
• Medallion Architecture Implementation
• 100% Hands-on Practical Sessions
• Production-Ready ETL Pipelines
• ADF & ETL from Basics to Advanced
• Interview Preparation
• Assignments & Practice Labs
• 100% Practical • No Unnecessary Theory
• Learn Like You’re Working in a Real Company