#Data Analyst

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 !

✅ SQL for Data Analysis & Reporting
✅ Advanced Excel, Pivot Tables, Dashboards
✅ Power BI for Interactive Visualizations
✅ Data Cleaning with Power Query
✅ Python: Pandas, NumPy, Visualization
✅ Statistics, Exploratory Data Analysis (EDA)
✅ Business Intelligence & Storytelling
✅ Real-Time Projects with Case Studies
✅ Resume Building, Portfolio & GitHub Profile
✅ 1:1 Mentorship & Interview Preparation

Module 1: SQL Server TSQL (MS SQL) Queries

Ch 1: Data Analyst Job Roles

Introduction to Data
Data Analyst Job Roles
Data Analyst 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 PK to Tables
Adding FK 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
Stored Procedures, Tuning

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 Blockin
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
Join Queries & 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: Tasks, Solutions
Case Study 2: ECommerce: Task, Solutions
Chapter Wise Assignments: Solutions
Dailly Assignments: Review (Feedback)
Weekly Mock Interview: Feedbacks

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]

Ch 14: Weekly Mock Interview Review meet ++ 1:1 Resume Meet

Brochure Download Request a Callback

Trainer Mr. Sai Phanindra Tholeti – 20 Years of Real-Time Experience | Microsoft, Deloitte Alumnus | Data Analyst and AI Expert

Trainer Sai Phanindra Tholetti – 20+ Years Expert in Power BI and Data Analytics | SQL School Training Institute

What is the Data Analyst course?

This program trains you to analyze data, build dashboards, use AI tools, write SQL queries, perform ETL, design Power BI reports, and apply Python for data analytics. It is fully job-oriented with 100% hands-on practice.

Who should join this Data Analyst course?

Anyone — freshers, non-IT learners, working professionals, and career switchers. The course starts from basics of data, databases, SQL, analysis, and reporting. No prior technical experience is required.

What are the modules included in this training?

Module 1: MSSQL & TSQL (3 Weeks, 2 Case Studies)
Module 2: Power BI with AI & CoPilot (4 Weeks, 4 Case Studies)
Module 3: Python for Data Analytics (3 Weeks, 1 Case Study)
Module 4: Realtime Projects + Excel + PL-300 + 1:1 Resume + Mock Interviews