Ch 1: SQL Database Job Roles

• Database Intro
• OLTP, DWH, OLAP
• DBMS Basics
• Data Stack 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
• Auto Detection of Data Types
• 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 & Advanced 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…

Project Implementations:

• HealthCare Database
• DB & Table Design
• Data Validations
• Query Design
• Query Tuning
• Stored Procedures
• Functions
• Excel Analytics

Ch 1: Power BI Intro, Installation

• Power BI & Data Analysis
• Power BI Eco System
• Power BI Design Tools
• Power BI Installation

Ch 2: Report Design Concepts

• Basic Report Design (PBIX)
• Data Points, Spotlight
• Visual Interactions & Edits
• Focus Mode, PDF Exports

Ch 3: Grouping, Hierarchies

• Creating Groups: Lists
• Creating Groups: Bins
• Hierarchies & Drill-Downs
• Drill Up, Conditional DrillDown

Ch 4: 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 5: Filters & Drill Thru

• Power BI Filters
• Basic, Top & Advanced
• Visual Filters, Page Filters
• Report Level Filters, Clear Filter
• Drill Thru Filters & Usage

Ch 6: Bookmarks, Buttons

• Power BI Bookmarks
• Images: Actions, Bookmarks
• Buttons: Actions, Bookmarks
• Page to Page Navigations
• Score Cards, Master Pages

Ch 7: SQL DB Access & Big Data

• SQL DB Access, Queries
• Storage Modes: Direct Query
• Formatting & Date Time
• Storage Modes in Power BI
• Data Modeling & Formatting

Ch 8: Power BI Visualizations

• Charts, Bars, Lines, Area
• Tree Maps & Axis Items
• Funnel, Card, Mult-Row Card
• Pie Charts & Waterfall
• Scatter Chart, Play Axis
• Infographics, Classifications

Ch 9: Power Query Transformations – 1

• Power Query (Mashup)
• ETL Transformations in PBI
• Table Combine Options
• Merge, Union All Options
• Missing Values, Duplicate Records
• Wrong Data Types, Outliers
• Close, Apply & Visualize

Ch 10: Power Query Transformations – 2

• Group By Transformation
• Aggregate, Pivot Operation
• Reverse Rows, Count Rows
• Data Cleaning, Null Handling
• Data Type Detection, Change
• Rename, Replace, Move
• Fill Up, Fil Down

Ch 11: Power Query Transformations – 3

• String / Text Transformations
• Split, Merge, Extract, Format
• Numeric and Date Time
• Add Column & Expressions
• Column From Examples

Ch 12: Power Query Transformations – 4

• Parameters in Power Query
• Static Parameters, Defaults
• Dynamic Dropdowns, Lists
• Linking with Table Queries
• Step Edits, Type Conversions

Ch 13: Power BI Cloud & Fabric

• Power BI Cloud, Microsoft Fabric
• Microsoft Fabric Concepts
• Fabric One Lake (DWH, LH, etc.)
• Microsoft Fabric Workspace
• Power BI Desktop Connections
• Report Uploads (PBIX)
• Report Edits, Semantic Models

Ch 14: Power BI Cloud Dashboards

• Power BI Dashboards
• Dashboard Creation, Usage
• Pin Visuals, Pin LIVE Pages
• Add Image, Video Tiles
• Q&A & Pin Tiles

Ch 15: Power BI Cloud Operations

• Report Shares, Alerts
• Subscriptions, Exploration
• Downloads & Edits
• Report Cloning in Cloud
• QR Codes, Web Publish
• Lineage & Metrics

Ch 16: Power BI Cloud Gateways

• Data Gateways, Data Refresh
• Install, Configure Gateways
• Data Refresh & Scheduling
• Gateway Optimizations
• Incremental Refresh
• Large Dataset Optimization

Ch 17: Power BI Cloud Apps

• Power BI Apps: Creation
• App Sections & Content
• Audience & App Security
• App Updates, Favorites
• App URL, End User Access

Ch 18: Power BI Report Server, RDL

• Power BI Report Server
• RS Config Tool Options
• Report Database, TempDB
• Web Service & Server URL
• Report Builder Tool
• Paginated Report (RDL)
• RDL Report Publish

Ch 19: DAX Concepts & Calculations

• DAX Concepts: Intro & Realtime Need
• DAX Columns: Creation, Use
• DAX Measures: Creation, Use
• DAX Functions: IIF, ISBLANK
• SUM, CALCULATE Functions

Ch 20: DAX Quick Measures

• Quick Measures in Power BI
• Running Totals
• Star Rating Calculations
• DAX Measures in Data View
• DAX in Cloud Reports

Ch 21: Data Modelling

• Dimensions Tables
• Fact Tables & DAX Measures
• Data Models & DDAX Joins
• Star & Snowflake Schemas
• Many-to-Many Relationships
• Calculation Groups

Ch 22: DAX Joins, Variables

• CALCULATEX & Variables
• COUNT, COUNTA, etc..
• SUM, SUMX, etc..
• SELECTED MEMEBER
• Filter Context, RETURN

Ch 23: DAX Models & Calculations

• VAR, SWITCH, SUMMARIZE
• TREATAS, USERELATIONSHIP
• CROSSFILTER, GENERATE
• RANKX, TOPN, WINDOW
• OFFSET, INDEX

Ch 24: 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 25: DAX – Row Level Security

• RLS: Row Level Security
• Data Modelling & Roles
• Add Cloud Users & KPIs
• CoPilot with DAX

Ch 26: DAX – Analytical Reports

• DAX with Excel
• Analytical Reports
• Virtual Cube Concepts
• Cross Filter Reporting
• Alerts, Data Activator

Ch 27: PL 300 Exam Guidance

• PL 300 Exam Guidance
• Exam Samples
• Exam Scenarios

Realtime Project: Enterprise Healthcare Data & Analytics Platform
Project Objective
Design and implement a modern Healthcare Data Platform using Power BI Analytics and Reporting services
to process patient, hospital, clinical, and operational data for reporting, analytics, and decision-making.
Technologies Used

• SQL Server
• MS Excel
• Parquet
• CSV
• PDF
• Azure

Learning Outcomes
After completing this project, you can confidently showcase experience in:

• Power BI Reporting
• Power BI Data Analytics
• Business Process Understanding
• Performance Optimization
• End-to-End Power BI Implementation in Cloud

Ch 1: Python Introduction

• Python Introduction
• Python Versions
• Python Job Roles
• Python for Data Analysts
• Python for Data Engineers
• Python for Data Scientists
• Python for Data Science Engineers

Ch 2: Python Architecture

•  Python Architecture
• PVM: Python Virtual Machine
• Compiler
• Byte Code
• Execution Process
• Resource Allocations
• Python Implementations

Ch 3: Python Installations

• Python Introduction
• Python Installations
• Anaconda Installation
• Python IDE & Usage
• Jupyter Notebooks

Ch 4: Python Print Statement

• Python Print Statement
• print(), print()
• Testing Case Sensitivity
• Single Line print()
• Multi Line print()
• print() with single quotations
• Debug with AI (AI Assistants)

Ch 5: Python Variables

• Python Variables
• Assigning values
• Purpose & Rules
• Variable Value Reads
• Multiple Variables & Print()

Ch 6: Python Operators

• Athematic *& Multiplier Operators
• Python String Literals
• Single, Double Quotes
• Format Strings (f string)
• Comparison, Indexing Operators

Ch 7: Python Data Types

•  Python Data Types
• Integer, Float, String Data Types
• Type Casting
• Type Identification
• Multi Value Assignments
• Python Built-In Classes (data types)

Ch 8: Python Lists

•  Creating Python Lists
• Printing List Items
• Print List Slices
• Length & Type
• list() method
• Empty Lists, Append
• Loops, List Updates

Ch 9: Python Dictionaries

• Python Dictionary
• Creating, Indexing Dictionaries
• Edit / Overwrite Key Values
• Lists inside Dictionaries
• Delete & Clear

Ch 10: Python Tuples

• Python Tuples
• Defining, Indexing
• Length(), Type()
• Mixed Values in Tuples
• Overwriting Tuples
• Tuple Class, (( ))

Ch 11: Python IF..ELSE Condition

• If..Else conditions
• if..elif..else & Shorthand if
• composite conditions
• Indent, pass statement
• in & negation operators
• range conditions

Ch 12: Python Loops (For)

•  Python For Loop
• For Loop @ Range
• For Loop @ Sequence Values
• Nested Loops
• Loop Control Statements
• Break, Continue, Paas

Ch 13: Python Loops (While)

• While Loop
• Termination Checks (Expressions)
• Variables, Logical Conditions
• Loop Conditions, Operators
• Exit Conditions
• iter() and Looping Options

Ch 14: Python Dataframes

• Dataframes: Creation
• Pandas Dataframes
• Dataframes From Single List
• Dataframes from Dictionary
• Display Dataframes, List Items
• Identify, Replace Nulls, NumPy

Ch 15: Python SQL DB Access

• SQL DB Access with Python
• import pandas.DataFrame
• pyodbc module, sql functions
• SQL DB Cursor Connections
• SQL Query Executions: DDL, DML
• Filters, Aggregations with SQL
• Dataframe Usage with SQL

Ch 16: Dataframe Transformations – 1

• Dataframe Transformations
• Concat & Append
• Merge Function
• Join with Multiple Dataframes
• Indexing Operations
• Data Type Checks, Conversions
• Loops with Dataframes

Ch 17: Dataframe Transformations – 2

• Pandas – Cleaning Data
• Replace, Transform Columns
• Data Discovery & Column Fill
• Identify & Remove Duplicates
• dropna(), fillna() Functions
• Data Plotting & matlib Lib

Ch 18: Python Functions & Lambda

• Python Functions & Usage
• Function Parameters
• Default & List Parameters
• Python Lambda Functions
• Recursive Functions, Usage
• Return & Print @ Lamdba

Ch 19: Python File Handling

• File Handling, Activities
• Loop, Write, Close Files
• Appending, Overwriting
• import os, path.exists
• f.open, f.write
• f.read, f.close

Realtime Case Study (Banking / Finance) For Data Analysis

Ch 1: Introduction to Snowflake

• Database, DWH Introduction
• Cloud Data Warehouse
• Cloud DWH Implementations
• Snowflake Cloud Intro
• Snowflake: SaaS Platform

Ch 2: Snowflake Concepts

• Snowflake Account (Cloud)
• Snowflake Components
• Snowflake Editions, Credits
• Snowflake Editions
• Virtual Private Edition (VPS)
• Snowflake Pricing

Ch 3: Architecture, Warehouse

• Compute Architecture
• Shared Disk Architecture
• CPU & Memory in Clusters
• Database Query & Data Cycle
• ColumnStore, Virtual Warehouse
• Classic UI with Snowflake
• Massively Parallel Processing

Ch 4: Snowflake Databases & Tables

• Snowflake Database Types
• Snowflake Table Types
• Retention Time, Connections
• Permanent, Transient Types
• CREATE TABLE AS SELECT (CTAS)

Ch 5: Time Travel, Recovery

• Time Travel in Snowflake
• Invoking Time Travel Feature
• Timestamp, Offset, Query ID
• Data Recovery, TIMESTAMP
• Fail Safe and UNDROP, OFFSET
• Transient Tables, Real-time

Ch 6: Schemas and Session Context

• Schema Creation Usage
• Permanent, Transient Schemas
• Managed Schemas in Snowflake
• Invoking Schemas & Cloning
• Session Context & Schema
• Data Loading with GUI

Ch 7: Snowflake Cloning

• Cloning with Snowflake
• Zero Copy, Schema Cloning
• Snapshot, Metadata
• Storage & Metadata Layer
• Real-time Considerations
• Transactions & Injection

Ch 8: Procedures & Views

• Procedures and Functions
• SQL and JavaScript & CALL
• sqlText:command
• Cursoring Data and Operations
• Dynamic DML with SPs
• RETURN, RETURNS Statements

Ch 9: Security Management

• Security with Snowflake
• Users & Roles in Snowflake
• Privileges and Groups
• Organization, Account, Users
• Creating, Using Roles, Users
• System Defined Roles Usage
• Role Hierarchy in Realtime
• Views For Security
• RBAC & DAC in Real-time

Ch 10: Snowflake Transactions

• Transaction ACID Properties
• Implicit, Explicit and Auto
• Durability and Data Storage
• current transaction() Usage
• to_timestamp_ltz and Usage
• Failed Transactions with SPs
• Transactions and SPs
• Scoped & INNER Transactions

Ch 11: Snowflake Streams & Audits

• Snowflake Streams & Usage
• Streams and DML Auditing
• Snapshot Creation, Offset
• METADATA Options & Streams
• Data Flow & Snowflake Streams
• Streams on Transient Tables
•  Time Travel with Stream Tables

Ch 12: Snowflake Tasks

• Tasks, Serverless Compute
• Tasks Tree: Root and DAG
• Tasks Schedules and RESUME
• User & Snowflake Managed
• CRON Syntax with Tasks
• Virtual Warehouse Concepts
• Multi Cluster Warehouse
• Auto Scale Options, Billing

Ch 13: SnowSQL and Variables

• SnowSQL Configurations
• DDL, DML & SELECT
• SnowSQL Command Line
• Variables and Batch Process
• DECLARE, LET, BEGIN & END
• EXECUTE IMMEDIATE, FOR
• Creating Virtual Warehouse
• Writing Output to Files

Ch 14: Snowflake Partitions, Stages

• Snowflake Partitions, Views
• Micro Partition with DML, CDC
• Cluster Key, Depth and Overlap
• Internal Partition Types & Usage
• List, Range and Hash Partitions
• Snowflake Stages, Types
• Internal and External Stages
• COPY Command, Bulk Loads

Ch 15: Azure / AWS External Stages

• Azure Storage Account, BLOB
• SAS: Shared Access Signature
• Using SAS Key and FILE PATH
• Azure Storage with BLOB
• COPY INTO Command Usage
• Snowflake Patterns & RegEx
• File Formats: Creation, Usage

Ch 16: Snow Pipes & Incr Loads

• SnowPipe Incremental Loads
• Azure Queues & Integrations
• Azure Active Directory
• External Stage, Enterprise AD
• Snow Pipes and Data Loads
• Incremental Data Loads
• File Format with Reg Expr

Ch 17: Power BI with Snowflake

• Power BI: Big Data Analytics
• Snowflake Data Access, Views
• Datawarehouse Access, Views
• Server URL & View Access
• Data Analytics with Views

Ch 18: SnowPro Certification Exam Guidance

• SnowPro Certification Overview & Exam Structure
• Certification Domains & Key Topics
• Important Snowflake Concepts for the Exam
• Topic-wise Exam Preparation Strategy
• Practice Questions & Scenario-Based Questions
• Mock Tests & Exam Readiness Assessment
• Common Exam Mistakes & Tips to Avoid Them
• Time Management & Question-Solving Techniques
• Revision Checklist & Last-Minute Preparation
• Guidance on Certification Registration & Exam Process

Ch 1: DBT Fundamentals

• What is Data Build Tool?
• DBT as a data transformation tool
• Importance of DBT in ELT workflows
• DBT Cloud for data transformations

Ch 2: DBT Models and Materializations

• Building models in DBT
• Types of materializations
• Table, view, incremental materializations
• Model configurations

Ch 3: DBT Jinja Templating

• Introduction to Jinja
• Using Jinja with DBT
• Macros and reusable code
• Implementing dynamic SQL

Ch 4: DBT Testing and Documentation

• Writing and executing tests
• Data quality checks
• DBT documentation and lineage graphs
• Generating DBT docs

Ch 5: DBT Seeds and Sources

• Using seeds for static data
• Defining and using sources
• Source freshness checks
• Integrating external data

Ch 6: DBT Deployment and CI/CD

• Deployment strategies for DBT
• Continuous integration and deployment
• Automating DBT workflows
• Version control with Git

Ch 7: DBT Best Practices

• Project structure recommendations
• Coding standards and guidelines
• DBT project optimization
• Performance tuning tips

Ch 8: Hooks in DBT

• Custom scripts to run at specific points
• Adding additional logic to streamline Snowflake
• Analyses and exploratory data workflows
• Ad-hoc analyses that do not get materialized

Ch 9: DBT Snapshots

• Managing historical data
• Implementing DBT snapshots
• Snapshot configuration
• Strategies for handling changes

Ch 10: DBT Packages and Extensions

• Leveraging DBT packages
• Using community packages
• Extending DBT functionality
• Integrations with other data tools

PROJECT 1: HEALTHCARE DATABASE
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…

Technologies:
SQL, Snowflake, Power BI

PROJECT 2: ECOMMERCE ANALYTICS

Project Requirement:
Build an end-to-end E-Commerce Analytics solution by ingesting, transforming, modelling,
analyzing, and visualizing customer, product, order, payment, and sales data.
Solve 25+ real-world E-Commerce business requirements using SQL, Python, Snowflake, DBT,
and Power BI.

Project Workflow:
Data Sources → Python Data Processing → Snowflake Data Warehouse → DBT
Transformations → Data Quality Testing → Analytics Models → Power BI Dashboard →
Business Insights

Project Operational Flow:
Customers → Products → Categories → Orders → Order Items → Payments → Shipping →
Returns → Snowflake → DBT Models → SQL Analytics → Power BI → Business Reports