#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

Data Analyst Training

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Module 1 : SQL Server & TSQL Queries

Ch 1: Database Intro & Job Roles

Database Introduction
Database Types: OLTP, DWH
DBMS & Realtime Use
DBMS Software & Purpose
SQL : Purpose & Use
SQL Server Versions, Editions
Job Roles & Responsibilities

Ch 2: SQL Server Installations

SQL Server 2022 Installations
SQL Server 2019 Installations
SSMS Tool Installation
Server Connections, Properties
Instance & Instance Types
Authentication Types
System Databases & Purpose

Ch 3: SQL Basics V1 (Commands)

Database, Tables & Columns
SQL Basics: Purpose
DDL Statements
DML Statements
DQL Statements
Verifications @ GUI
Basic SELECT Queries

Ch 4: SQL Basics V2 (Operators)

DDL Variants in MSSQL
DML Variants in MSSQL
INSERT & INSERT INTO
SELECT & SELECT INTO
Basic Operators in SQL
Special Operators in MSSQL
ALTER, TRUNCATE, DROP

Ch 5: Excel Data Imports

Data Imports with Excel
SQL Native Client
Order By: Asc, Desc
Order By with WHERE
TOP & OFFSET
UNION ALL
UNION, Data Appends

Ch 6: Schemas & Security

Schemas: Creation, Usage
Schemas & Table Grouping
Using Default Schema
Real-world Banking Database
Table Migrations @ Schemas
2 Part, 3 Part & 4 Part Naming
Verifying Schemas in UI

Ch 7: Constraints & Keys Basics

Need for Constraints, Keys
Null, Not Null Constraints
Unique Key Constraint
Primary Key Constraint
Foreign Key & References
Default Constraint & Usage
DB Diagrams & ER Models

Ch 8: Indexes Basics, Tuning

Indexes & Tuning
Clustered Index, Primary Key
Non Clustered Index & Unique
Creating Indexes Manually
Verifying Indexes
Composite Keys, Query Optimizer
Composite Indexes & Usage

Realtime Case Study 1

Ch 9: Joins Basics

Joins: Table Comaparisons
Inner Joins & Matching Data
Outer Joins: LEFT, RIGHT
Full Outer Joins & Audits
Cross Joins & Table Combinations
Joining more than 2 tables
Joining Tables with Aliases

Ch 10: Views & RLS

Views: Realtime Usage
Storing SELECT in Views
DML, SELECT with Views
RLS: Row Level Security
WITH CHECK OPTION
Database Audits & Metadata
Important System Views

Ch 11: 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 12: User Defined Functions

Using Functions in MSSQL
Scalar Value Functions
Inline & Multiline Functions
Parameterized Queries
Date & Time Functions
String Functions & Queries
Aggregated Functions & Usage

Ch 13: Triggers & Automations

Need for Triggers
DDL & DML Triggers
For / After Triggers
Instead Of Triggers
Memory Tables with Triggers
Data Replication, Automation
Disabling DMLs & Triggers

Ch 14: Transactions & ACID

Transaction Concepts in OLTP
Transaction Types in Realtime
Auto Commit, Explicit Transaction
COMMIT, ROLLBACK
Checkpoint & Logging
Lock Hints & Query Blocking
READPAST, LOCKHINT

Ch 15: Cursors & Fetch

Cursors: Realtime Usage
Cursor Declaration Types
Open Cursor, Close Cursor
Local & Global Cursors
Scroll & Forward Only Cursors
Static & Dynamic Cursors
Fetch, Absolute Cursors

Ch 16: CTEs & Tuning

CTE: Common Table Expression
Creating and Using CTEs
CTEs and In-Memory Processing
Using CTEs for DML Operations
Using CTEs for Data Retrieval
Using CTEs for Tuning
CTEs For Duplicate Row Deletion

Realtime Case Study 2

Ch 17: Relations, Normal Forms

Adding PK to Tables
Adding FK to Tables
Cascading Keys
Self Referencing Keys
Database Diagrams
Normal Forms : 1 NF, 2 NF
3 NF, BCNF and 4 NF

Ch 18: Self Joins, EXISTS

Joining same table
Correlated Queries
Joining Tables, Queries
Self Joins with WHERE
Self Joins with UNION
Self Joins with Order By
Self Joins with Views

Ch 19: Remote Joins

Working with Multiple Servers
Multi Server Access from SSMS
Linked Servers Creation, Tests
4 Part Naming Convention
Remote Data Access
RPC & RPC OUT
Remote Joins & Data Analysis

Ch 20: Sub Queries

Sub Queries Concept
Sub Queries & Aggregations
Joins with Sub Queries
Sub Queries with Aliases
Sub Queries with OrderBy
Sub Queries with WHERE
Sub Queries, Joins, Where

Ch 21: 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 22: 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 23: Data Types & Conversions

Integer Data Types
Character, MAX Data Types
Decimal & Money Data Types
Boolean & Binary Data Types
Date and Time Data Types
Table, SQL_Variant Types
Cast( ) and Convert( ) Functions

Ch 24: Window Functions, CASE

IIF Function and Usage
IIF with Tables, Joins
CASE Statement Usage
Window Functions (Rank)
Row_Number( )
Rank( ), DenseRank( )
Partition By & Order By

Realtime Case Study 3

Module 2 : Power BI

Ch 1: Power BI Intro, Installation

Power BI Eco System
Report Types & Usage
Power BI Tools, Cloud
Power BI Components
Power Query (M), DAX
Power BI: Co-Pilot & AI
Power BI Installations

Ch 2: Report Design Concepts

Basic Report Design (PBIX)
Get Data, Canvas (Design)
Data View, Data Models
Data Points, Aggregations
Focus Mode, Spotlight
PDF Exports From Power BI
ToolTip, PBIX Reports

Ch 3: Visual Interactions, PBIT

Data View Concepts
Visual Interactions & Edits
Limitations with Visual Edits
Creating Power BI Templates
CSV Exports & PBIT Imports
Optimizing Power BI : Caching
PBIX Versus PBIT

Ch 4: Grouping, Hierarchies

Power BI : Field Values
Field Value Groups
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
Integer, Character Slicers
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 of Data Points

Ch 7: Filters & Drill Thru

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

Ch 8: Bookmarks, Buttons

Power BI Bookmarks
Bookmarks Creation, Use
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
Storage Modes & Formatting
Azure (Big Data) Access

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, Reference
Group By Transformation
Aggregate, Pivot Operation
First Row as Header
Reverse Rows, Count Rows
Advanced Power Query Mode

Ch 13: Power Query: Column Tfn

Any Column Transformations
Change Data Type
Detect Data Type
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
Column From Examples
Step Edits, Type Conversions

Ch 16: Power BI Cloud: Publish

Power BI Cloud Concepts
Workspace Creation, Usage
Workspace Items
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
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
Dataset 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, Favorites
App URL, End User Access

Ch 21: Power BI Report Server

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)
SQL Database Access
SQL Queries For RDL
Tablix, Chart Wizards
Fields & Drill-Down
RDL Report Publish

Ch 23: DAX Concepts (Basics)

DAX Concepts (Introduction)
DAX : Realtime Use
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
Analyze in Excel (Cloud)
Excel Reports to Cloud

Ch 30: Introduction to CoPilot

AI Components in Power BI
Need for CoPilot
CoPilot Practical Uses
CoPilot with Desktop
CoPilot with Cloud
Need for AI Analytics (Fabric)

Ch 31: Realtime Project – Phase 1

Customer Requirement
Requirement Analysis
Project Planning
Creating Data Sheets
Creating Data Models
Scope of the Project
Data Sheets, Project Planning

Ch 32: Realtime Project – Phase 2

Report Design & Modelling
Power Query Implementation
DAX & Data Analytics
Power BI Cloud (Service)
Power BI Report Server
End User Take Aways
Implementation Phases

Ch 33: PL 300 Exam Guidance

PL 300 Exam Benefits
Data Analyst Exam Pattern
Type of Questions
Sample Questions, Answers
Mock Certification
Resume Guidance
Mock Interviews

Module 3 : Python Analytics

Ch 1. Python Introduction

Need for Data Analytics
Python in Data Analysis
History of Python
Python Versions
Python Implementations
Python Installations
Python IDE & Usage
Jupyter Notebooks

Ch 2. Python Basics, Architecture

Python Scripting Options
Basic Operations in Python
Python Scripts, Print()
Single, Multiline Statements
Adding Cells, Saving Notebook
Single, Multi Line Comments
Python : Internal Architecture
Compiler Versus Interpreter

Ch 3. Data Types & Variables

Integer / Int Data Types
Float & String Data Types
Boolean, Binary Types
Sequence Types: List, Tuple
Range, Complex & memview
Retrieving Data Type: type()
Multi Assignments & Casting
Unpack Collection, Outputs

Ch 4. Python Operators

Arithmetic, Assignment Ops
Comparison Operators
Logical, Identity Operators
Member, Bitwise Operators
Operator Precedence
If … Else Statement, Pass
Short Hand If, OR, AND
ELIF and ELSE IF Statements
Expressions, Ternary OPs

Ch 5: Python Loops, Iterations

Python Loop & Realtime Use
Python While Loop Statement
Break and Continue Statement
Using Print with While()
Iterations & Conditions
Exit Conditions & For Loops
Break, Continue & Range
__iter__() and __next__()
iter() and Looping Options

Ch 6: Python Collections

Python Collections (Arrays)
list() Constructor, print()
Python Tuples, Tuple Items
tuple() Constructor, Usage
Python Sets : Syntax Rules
Duplicates, Types, Ordered
Python Dictionaries: Usage
Changeable, Ordered Data
Dictionary Construct, type()

Ch 7: Python Functions

Python Functions & Usage
Function Parameters
Arguments, **kwargs
Default & List Parameters
Python Lambda Functions
Anonymous Functions
Recursive Functions, Usage
Return & Print @ Lamdba

Ch 8: Python Classes & Arrays

Python Classes & Objects
__init__() Function
__str__() Function
Self Parameters & Objects
Python Inheritance & Classes
Parent & Child Classes
__init__() & super() Function
Polymorphism in Python

Ch 9: Python Modules

import Python Modules
Variables in Modules
Built In Modules & dir
datetime module in Python
Date Objections Creation
strftime Method & Usage
imports & datetime.now()
Using Python Constructors

Ch 10: : Python JSON & RegEx

JSON Concepts, Usage
Dictionary & import json
Python Objects into JSON
Formatting & Ordering
json.dumps, print options
Python Regular Expressions
RegEx Module & Function
search() & span() , Strings
Using RegEx with JSON

Ch 11: Python User Inputs & TRY

Try Except, Exception Handling
NameError Resolution
Python Finally Block, Usage
Raise an exception method
TypeError, Scripting in Python
Python User Inputs
Python Index Numbers
Named Indexes, Usage
input() & raw_input()

Ch 12: Python File Handling

File Handling, Activities
r, a, w, x modes
t, b Operations
Read Only Parts
Loop, Write, Close Files
Appending, Overwriting
import os, path.exists
f.open, f.write
f.read, f.close

Ch 13: Data Analytics – Pandas

Python Modules & Pandas
Pandas Codebase & Usage
Installation of Pandas
import pandas.DataFrame
Checking Pandas Version
Pandas Series, arrays
Labels : Creation, Use
series(), print()

Ch 14: Data Analytics – DataFrames

Indexes & Named Options
Locate Row and Load Rows
Row Index & Index Lists
Load Files Into a DataFrame
pd.read_csv() Function
pd.options.display.max_rows
df.to_string() Function
tail() & null() Function

Ch 15: Pandas Transformations

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

Ch 16: SQL DB & Python – 1

SQL & Databases
Azure Data Studio Tool
sp_execute_external_script
Input Data & Result Sets
DDL & DML with Python
SQL_out, SQL_in
Variables & Parameters
Versions, Package List
WITH RESULT SETS Options

Ch 17: SQL & Python – 2

pandas.Series with SQL DBs
Indexing Methods in Realtime
Convert series to data frame
Output values into data.frame
pymssql package in SQL Server
pip list & Package Manager
Python runtime, Py Package
pymssql.connect & Usage
Cursor Variables & Usage

Ch 18: Realtime Case Study

Module 4: Advanced Excel & Data Analytics

Ch 1: Basic Functions

Excel Analytics
SUM, AVERAGE, AGGR
COUNT, COUNTA
Absolute, Mixed
Relative Referencing

Ch 2: Formatting and Proofing

Currency Format
Format Painter
Formatting Dates
Custom and Special Formats
Formatting Cells

Ch 3: Functions

SUMIF, SUMIFS, COUNTIF
COUNTIFS, AVERAGEIF
AVERAGEIFS, NESTED IF
IFERROR STATEMENT
AND, OR, NOT

Ch 4: Protecting Excel

File Level Protection
Workbook
Worksheet Protection
Security Concepts
Realtime Issues, Solutions

Ch 5: Text Functions

Upper, Lower, Proper
Left, Mid, Right
Trim, Len, Exact
Concatenate
Find, Substitute

Ch 6: Date & Time Functions

ToCh, Now
Ch, Month, Year
Date, Date if, Date Add
EOMONTH
WeekCh Functions

Ch 7: Adv. Techniques

Paste Formulas
Paste Formats
Paste Validations
Transpose Tables
Excel Analytics
Excel Expressions

Ch 8: New in Excel 365 – 1

Charts – Tree map & Waterfall
Sunburst, Box and whisker Charts
Combo Charts – Secondary Axis
Adding Slicers Tool in Pivot & Tables
Using Power Map and Power View
Forecast Sheet, park lines

Ch 9: New in Excel 365 – 2

Using 3-D Map
New Controls in Pivot Table
Various Time Lines
Auto complete a data range
Quick Analysis Tool
Smart Lookup manage Store

Ch 10: Printing Workbooks

Setting Up Print Area
Customizing Headers
Templates
Print Titles – Repeat Rows
Real-world Considerations

Ch 11: Sorting and Filtering

Filtering on Text
Numbers & Colours
Sorting Options
Advanced Filters
Filter Criteria

Ch 12: What If Analysis

Goal Seek
Scenario Analysis
Data Tables
PMT Function
Solver Tool

Ch 13: Logical Functions

If Function
How to Fix Errors – if error
Nested If
Complex if
Excel Functions
Excel Math Options

Ch 14: Data Validation

Number, Date & Time
Text and List Validation
Custom validations formulas
Dynamic Dropdowns
Realtime Considerations
Smooth User Interface

Ch 15: Lookup Functions

V lookup / H Lookup
Index and Match
Nested V Lookup
Reverse Lookup
Worksheet linking
V lookup with Helper

Ch 16: Pivot Tables – 1

Creating Simple Pivot Tables
Classic Pivot table
Choosing Field
Filtering PivotTables
Modifying PivotTable Data
Grouping
Calculated Fields

Ch 17: Pivot Tables – 2

Array with IF, LEN
MID function formulas.
Array with Lookup functions.
Various Charts
SLICERS, Filter data
Manage Primary Axis
Manage Secondary Axis

Ch 18: Excel Dashboard

Planning a Dashboard
Adding Tables
Charts to Dashboard
Dynamic Contents
Dashboard URLs
Dashboard Shares
Dashboard in Cloud

Ch 19: VBA Macro – 1

Using Outlook Namespace
Send automated mail
Outlook Configurations
MAPI Options
Worksheet Operations
Workbook Operations

Ch 20: VBA Macro – 2

Merge Worksheets
Macro Options
Merge excel files
Split worksheets
VBA Worksheet copiers
Realtime Usage

Ch 21: Agile Features

Using Agile
Business Analytics Options
BA Job Roles
BA Job Requirements
Technical Specifications
RFPs and process
Realtime Job Roles

Module 5: AI, CoPilot with Data Analytics

Chapter 1: Fundamental AI Concepts

AI: Artificial Intelligence
Real-time Implementation
Understand Computer Vision
Understand Natural Language Processing
Document Intelligence and Knowledge Mining
Understand Generative AI
Challenges and Risks with AI
Understand Responsible AI

Chapter 2: Fundamentals of AI services

AI Services on Azure platform
Create Azure AI Service Resources
Use Azure AI services
Understand Authentication for Azure AI services
Exercise – Explore Azure AI Services

Chapter 3: Computer Vision

Images and image processing
Machine learning for computer vision
Azure AI Vision
Exercise – Analyze images in Vision Studio

Chapter 4: Natural Language Processing

Understand Text Analytics
Text Analysis in Azure
Exercise – Analyze text with Language Studio

Chapter 5: Document Intelligence and Knowledge Mining

Introduction to Document Intelligence
Knowledge Mining
Explore capabilities of document intelligence
Receipt Analysis on Azure
Exercise – Extract from data in Document Intelligence Studio

Chapter 6: Generative AI

What is generative AI?
What are language models?
Using language models
What are copilots?
Considerations for Copilot prompts
Extending and developing copilots
Exercise – Explore Microsoft Copilot

Chapter 7: Generative AI in Azure

Generative AI – Capabilities within AI in Azure
Azure Implementation of Gen AI
Processing Images, Codes and more

Chapter 8: CoPilot with Data Analytics – 1

Implementing AI in Cloud
Co-Pilot Concepts in Big Data
AI with Azure
AI with Azure SQL Database
Automated Query Tuning Concepts (OLTP)

Chapter 9: CoPilot with Data Analytics – 2

AI with Power BI
CoPilot with Power BI – Power Query
CoPilot with Power BI – Cloud
CoPilot with Power BI – DAX
CoPilot with Power BI – Excel Analytics

Data Analyst Certificate of Completion – SQL School | MSME & ISO Certified Institute | August 2025

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Data Analyst Training FAQ's

What is Data Analyst Job Role?

Data Analyst refers to the role that focuses on data extraction, transformation, analysis, and reporting. It involves collecting data from multiple sources (Apps, Files, Databases, Forms, IoT Devices, etc..), applying data mashup operations, performing statistical evaluations, and generating business insights and reports for informed decision-making.

What are the Job Roles of a Data Analyst?

💼 Top Job Roles:

Managing Big Data & Data Analysis
Managing IAM [Identity & Access Management]
Managing Data Warehouse (DWH) Databases for Reporting
Secure & Optimize Data Warehouse (DWH) Reports
Orchestrate the Data Flow for Analytics
Data Governance, Policy Management and more .. !

What does our Data Analyst Training course contain?

The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Power BI
👉🏻Module 3: Python Analytics

Who can join this course?

Freshers looking to start a career in data or analytics
Working professionals wanting to shift to Python, Data Science, or Data Analyst roles
Students from any background interested in tech and data
IT and Non-IT professionals aiming to upskill
Anyone with basic computer knowledge and a passion for learning

No prior coding experience is required. All concepts are taught from scratch.

What training modes are available?

Option 1: LIVE Online Training (100% Interactive, step by step, assignments)

Option 2: Self Paced Videos (100% practical, step by step with concept wise assignments)

You may choose any one of these options, same curriculum!

I (Trainer) shall be available for doubts and clarifications, assignment check and review.

Why should I choose SQL School for Data Analyst training?

👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!

👉🏻 100% results with on-time practice. Daily Tasks for every session.

👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.

👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.

Why Choose SQL School

Why Choose SQL Student learning coding on laptop in a futuristic environment representing career-focused database and data engineering training at SQL School

100% Real-Time and Practical
ISO 9001:2008 Certified
Concept wise FAQs
TWO Real-time Case Studies, One Project
Weekly Mock Interviews
24/7 LIVE Server Access
Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support
Realtime Project Solution
MS Certification Guidance