#MySQL Developer

MySQL Developer plays a vital role in designing, developing, and optimizing reliable database systems. They work on schema design, complex queries, stored procedures, and performance tuning to ensure scalability and security. With the growing demand for data-driven applications, learning MySQL offers excellent career opportunities in web development, enterprise solutions, and cloud-based platforms.

✅ SQL Queries, Joins, Subqueries
✅ Stored Procedures & Functions
✅ Triggers, Views & Transactions
✅ Normalization, Database Design
✅ Indexing & Query Optimization
✅ Dynamic SQL & User Variables
✅ JSON, XML Data Handling
✅ Query Tuning Practices
✅ Real-Time PostgreSQL Projects
✅ 1:1 Mentorship & Career Prep

Module 1: SQL Server TSQL (MS SQL) Queries

Ch 1: Data Engineer Job Roles

Introduction to Databases
Data Architect Job Roles
Data Architect Challenges
Data Architect technologies
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

Normal Forms: 1 NF, 2 NF
3 NF, BCNF and 4 NF
Adding Keys to Tables
Cascading Keys
Self Referencing Keys
Data Modelling (OLTP)
ER Models

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
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

Module 2: Azure Data Engineer

Section 1: ADF, Synapse

Ch 1: Azure ETL, DWH Introduction

Data Warehouse (DWH)
Cloud Concepts: IaaS, PaaS
SaaS & Azure Cloud Concepts
Azure Resources & Groups
Storage, ETL, IoT Resources

Ch 2: Azure Intro, Azure SQL

Azure SQL Server, SQL DB
Azure SQL Database (OLTP)
Azure SQL Pool (DWH)
Connections from SSMS Tool
Connections from ADS Tool
Pause / Resume SQL Pool
Source Data Configurations

Ch 3: Azure Synapse (DWH)

Synapse Pool Architecture
Control Node, Compute Node
DMS & Partitioned Tables
Creating Tables with TSQL
Distributions: RR, Hash, Repl
Big Data Loads with TQL
Important DMFs & DMVs

Ch 4: Azure Data Factory (ADF)

Need for ADF & Pipelines
Data Orchestration with IR
Integration Runtime Engine
Linked Services, Datasets
Pipelines: Copy Data Activity
Data Flow Activity with IR

Ch 5: Azure SQL DB Loads

ADF: Author
Azure SQL Database Reads
Azure SQL Pool Writes
Synapse Analytics with IR
Pipeline Design, Validation
Pipeline Runs, Monitoring

Ch 6: BLOB Data Loads

Azure Storage Account
Azure BLOB Containers
BLOB Storage in ADF
Synapse Analytics with IR
ADF Pipeline Edits
Pipeline Runs, Monitoring

Ch 7: Pipeline Settings

ADF Pipeline Settings
Staging : Advantages
Reliable Logging
Best Effort Logging
DIU & DOCP with IR
Compressions, Health Check

Ch 8: File Incremental Loads

File Incremental Loads
Storage Account, Data Lake
Binary Copy, Schema Drift
Staging Concept in ADF
Initial, Incremental Loads
Schema & Data Changes

Ch 9: 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 Runs, Activity IDs

Ch 10: ADF Data Flow – 1

Data Flow Transformations
Spark Clusters for Debugging
Optimized Clusters, Preview
Conditional Split, SELECT
Sort, Union Transformations
Pipelines with Data Flow

Ch 11: ADF Data Flow – 2

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

Ch 12: ADF Data Flow – 3

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

Ch 13: ADF Data Flow – 4

Lookup Transformation
Cache Lookup
Inline Datasets
Data Validations
Lookup Versus Joins
Broadcast Options

Ch 14: ADF Metrics, Alerts

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

Ch 15: ADF Parameters, Security

Linked Service Parameters
Creating Logins
Users and ETL Permissions
Parameterize Logins
Parameterize Users
Dynamic Linked Services

Ch 16: Parameters, SCD & ETL

ADF Templates in Realtime
Implementing ADF SCD
Table Incremental Loads
Control Tables, Watermarks
Pipeline Parameters, SPs
Dynamic Data Sets, SCD

Ch 17: Synapse Analytics

Azure Synapse Analytics
Dedicated SQL Pools
TSQL: Stored Procedures
Synapse Pipelines, Tuning
SP Activity in Pipelines, Jobs
Comparing ADF & Synapse

Ch 18: CI CD with GitHub

Creating Github Account
GIT: Main, Branches
Connecting with ADF
Version Changes
Builds and Deployments
CI-CD Integrations

Section 2: ADLS, loT, Migrations

Ch 1: Azure Storage Security, ADF

Access Keys & Admin Access
SAS Keys Generation, Ips
Azure AD Users, Groups
IAM & RBAC with Entra Users
ACLs and ADLS Security
ADF with Azure Storage Security

Ch 2: Azure SQL DB Migrations

On-Premise SQL DB bacpac
Azure SQL Deployment
Azure Storage from SSMS
Azure SQL DB Migration
Migration Verifications
Testing Migrations in SQL

Ch 3: Azure Tables & ADF

Azure Tables
Entities and Properties
Storage Service Operations
OData Queries & Filters
Data Loads with ADF

Ch 4: Azure Stream Analytics

Azure IoT Hubs & Devices
APIs with Connection Strings
Azure Steam Analytic Jobs
Inputs, Outputs, SAQL Query
LIVE Feed: JSON, AVRO Files
Watermark & LIVE Streams

Ch 5: Azure Key Vaults

Azure Encryptions at REST
SMK & CMK Encryptions
Azure Key Vaults & Keys
Key Access Policies
Rest, Transit Encryptions
Realtime Considerations

Ch 6: Azure Logic Apps

Azure Logic Apps
Consumption Logic
Standard Logic
Logic App Connectors
Triggers & Parallel Branches
Schedules & Automations

Section 3: Python, Spark, PySpark, Databricks

Ch 1: Databricks Introduction

Cloud ETL, DWH
Cloud Computing
Databricks Concepts
Big Data in Cloud

Ch 2: Databricks Architecture

Unity Catalog, Volume
Spark Clusters
Apache Spark and Databricks
Apache Spark Ecosystem
Compute Operations
Hadoop, MapReduce, Apache Spark

Ch 3: Unity Catalog

Unity Catalog Concepts
Workspace Objects
Databricks Notebooks
Databricks Workspace UI
Organizing Workspace Objects
Creating Volumes
Spark Table Creations
UI : Limitations

Ch 4: Unity Catalog Operations, Spark SQL – 1

Spark SQL Notebooks
Creating Catalog
Creating Schemas, Tables
Spark Data Types
Data Partitioning
Managed Tables
SQL Queries with the PySpark API
Union, Views in Spark
Dropping Objects
External Tables, External Volumes
Spark SQL Notebooks: Exports, Clone

Ch 5: Spark SQL Notebooks – 2

Math, Sort Functions
String, DateTime Functions
Conditional Statements
SQL Expressions with expr()
Volume for our Data Assets
File Formats, Schema Inference
Spark SQL Aggregations

Ch 6: Python Concepts – 1

Python Introduction
Python Versions
Python Implementations
Python in Spark (PySpark)
Python Print()
Single, Multiline Statements

Ch 7: Python Concepts – 2

Python Data Types
Integer / Int Data Types
Float, String Data Types
Arithmetic, Assignment Ops
Comparison Operators
Operator Precedence
If … Else Statement
Short Hand If, OR, AND
ELIF and ELSE IF Statements

Ch 8: Python Concepts – 3

Python Lists
List Items, Indexes
Python Dictionaries
Tables Versus Dictionaries
Python Modules & Pandas
import pandas.DataFrame
Pandas Series, arrays
Indexes, Indexed Lists

Ch 9: PySpark – 1

Dataframes with SQL DB
Pandas Dataframes
Dataframe()
List Values, Mixed Values
spark.read.csv()
spark.read.format()
Filtering DataFrames
Grouping your DataFrame
Pivot your DataFrame

Ch 10: PySpark – 2

DataFrameReader
DataFrameWriter Methods
CSV Data into a DataFrame
Reading Single Files
Reading Multiple Files
Schema with an SQL String
Schema Programmatically

Ch 11: PySpark – 3

Writing DataFrames to CSV
Working with JSON
Working with ORC
Working with Parquet
Working with Delta Lake
Rendering your DataFrame
Creating DataFrames from Python Data Structures

Ch 12: PySpark Transformations – 1

Data Preparation
Selecting Columns
Column Transformations
Renaming Columns
Changing Data Types
select() and selectExpr()
Column Transformation
withColumn()

Ch 13: PySpark Transformations – 2

Basic Arithmetic and Math Functions
String Functions
Datetime Conversions
Date and Time Functions
Joining DataFrames
Unioning DataFrames
Joining DataFrames

Ch 14: PySpark Transformations – 3

Filtering DataFrame Records
Removing Duplicate Records
Sorting and Limiting Records
Filtering Null Values
Grouping and Aggregating
Pivoting and Unpivoting
Conditional Expressions

Ch 15: Medallion Architecture

Medallion Architecture
Aggregated Data Loads
Broze, Silver and Gold
Temp Views
Spark Tables (Parquet)
Work with File, Table Sources

Ch 16: Delta Lake – 1

Storage Layer
Delta Table API
Deleting Records
Updating Records
Merging Records
History and Time Travel

Ch 17: Delta Lake – 2 (SCD)

Schema Evolution
Delta Lake Data Files
Deleting and Updating Records
Merge Into
Table Utility Commands
Exploratory Data Analysis
Incremental Loads
Old History Retention
Delta Transaction Log

Ch 18: Widgets

Text Widgets
User Parameters
Manual Executions
Lake Bridge
Databricks BridgeOne

Ch 19: Lake Flow Jobs

Worksflows & CRON
Job Compute, Running Tasks
Python Script Tasks
Parameters into Notebook Tasks
Parameters into Python Script Tasks
Concurrent Executions, Dependencies
Branching Control with the If-Else Task

Ch 20: Databricks Tuning

How Spark Optimizes your Code
Lazy Evaluation
Explain Plan
Inspecting Query Performance
Caching, Data Shuffling
Broadcast Joins
When to Partition
Data Skipping
Z Ordering
Liquid Clustering
Spark Configurations

Ch 21: Version Control & GitHub

Local Development
Runtime Compatibility
Git and GitHub Pre-requisites
Git and GitHub Basics
Linking to GitHub & Databricks
Databricks Git Folders
Project Code to GitHub
Adding Modules to the Project Code
Databricks Job Updates, Runs

Ch 22: Spark Structured Streaming

Streaming Simulator Notebook
Micro-batch Size
Schema Inference and Evolution
Time Based Aggregations, Watermarking
Writing Streams
Trigger Intervals
Delta Table Streaming Reads, Writes

Ch 23: Auto Loader

Reading Streams with Auto Loader
Reading a Data Stream
Manually Cancel your Data Streams
Writing to a Data Stream
Workspace Modules

Ch 24: Lake Flow Declarative Pipelines

Delta LIVE Tables
Data Generator Notebook
Pipeline Clusters
Databricks CLI
Data Quality Checks
Streaming Dataset “Simulator”
Streaming Live Tables

Ch 25: Security: ACLs

Overview of ACLs
Adding a New User to our Workspace
Workspace Access Control
Cluster Access Control
Groups & LakeBridge

Ch 26: Realtime Project 2 @ Ecommerce / Banking / Sales

👉 Detailed Project Requirements
👉 Project Solutions
👉 Project FAQs
👉 Project Flow
👉 Interview Questions & Answers
👉 Resume Guidance (1:1)

Module 3: Snowflake (Cloud ETL, DWH)

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 DB & Tables

DB Objects and Hierarchy
DB Creation with Snowflake
Snowflake Tables and Usage
Retention Time, Connections
Permanent, Transient Types
CREATE TABLE AS SELECT

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: Constraints & Data Types

Constraints & Validations
NULL, NOT NULL Properties
Keys & Constraints, Usage
Inline, Out Of LineConstraints
ENFORCED Constraints
Snowflake Data Types

Ch 8: Snowflake Cloning

Cloning with Snowflake
Zero Copy, Schema Cloning
Snapshot, Metadata
Accessing, Clone
Storage & Metadata Layer
Real-time Considerations

Ch 9: Snowflake Procedures

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

Ch 10: 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, Dependency
RBAC & DAC in Real-time

Ch 11: 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 12: Snowflake Streams & Audits

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

Ch 13: Snowflake Tasks, Partitions

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

Ch 14: 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 15: Snowflake Partitions, Stages

Snowflake Partitions, Use
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 16: Azure & 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 17: 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

Module 4: Power BI

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 Navigations
Score 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: Power BI AI, CoPilot

AI Components in Power BI
CoPilot Practical Uses
CoPilot with Desktop
CoPilot with Cloud
Need for AI Analytics (Fabric)
PL 300 Exam (Microsoft Certified Data Analyst) Guidance
PL 300 Exam Mocks

Module 5: ERWIN

Ch 1: Introduction

Data Modeling Concepts
Data Modeling Methods
Typographical Conventions
ERWIN Tool Installations

Ch 2: Information Systems, Data Modeling

Data Modeling Concepts
Data Modeling Sessions
Session Roles
IDEFX1 Modelling Methodology

Ch 3: Modeling Architecture

Modeling Architecture
Logical Modeling
Physical Modeling
Entity Relationship Diagrams
Key Based Models
Transformation Models

Ch 4: Logical Modeling

Local Models Construction
ER Diagrams
Entities & Attributes
Many to Many Relationships
Design Validations
Data Models in Realtime

Ch 5: Key Based Data Models

Key Types
Entity, Non Key Areas
Primary Key Selection
Alternate Key Attributes
Inversion Entry Attributes

Ch 6: Relationships in ER Model

Relationship, Foreign Key Attributes
Dependant, Independent Attributes
Identifying Relations
Non Identifying Relations
Role Names

Ch 7: Naming Conventions

Entity Names
Attribute Names
Synonyms
Hamonyms
Aliases
Entity Definitions
Definition References
Circularity
Business Glossary Construction
Attribute Definitions
Validation Rules
Role Names
Definition and Business Rules

Ch 8: Relationships

Relationship Cardinality
Referential Integrity (RI)
Additional Relationship Types
Many to Many Relationships
N-ary Relationships
Recursive Relationships
Subtype Relationships
Inclusive Relationships
Exclusive Relationships
IDEF1X, IE SubType Notation

Ch 9: Normalization Issues, Solutions

Normal Forms Concepts
Common Design Problems (CDP)
Repeating Data Groups
Repeating Attributes
Repeating Facts
Conflicting Facts
Derived Attributes
Missing Information
Unification
Normal Forms Support Levels

Ch 10: Physical Data Models

Physical Data Models Concepts
Physical Data Models Components
Logical versus Physical Data Models
Dependant Entities Classifications
DBMS Models
DWH Models
SQL DB Configurations

Module 6: End to End Project

👉 Project Requirement (Ecommerce / Banking)

👉 Project Solution (Detailed)

👉 Project FAQs, Resume Guidance

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