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Data Analytics Course

Data Analytics Course in Gurgaon – With Placement Focused Course

Our Data Analytics Course in Gurgaon is designed for students, fresher, and working professionals who want to understand how the data works in real-world jobs. Data Analytics Classes in Gurgaon begins with basic concepts & then progresses towards advanced tools.

Duration: 12 - 15 Week | Mode: Live + Recorded Sessions

Watch Data Analytics Demo Class

Attend our Data Analytics Training in Gurgaon demo session to understand how live classes work before you join the course and enroll.

Our Recently Placed Students

Gita Singh

Placed at Accenture

Suman Sharma

Placed at TCS

Manoj Prasad

Placed at Deloitte

Vinod Sharma

Placed at Wipro

Pawan Kumar

Placed at IBM

Gopal Singh

Placed at Infosys

Ankit Mishra

Placed at Microsoft

Rohit Shah

Placed at Capgemini

Online Data Analytics Course in Gurgaon

About the Data Analytics Course in Gurgaon

The Data Analytics Classes in Gurgaon is structured in such a manner that it will provide you with the necessary tools as well as the logic necessary for any data-related task. Data Analytics Classes in Gurgaon will cover data collection, processing, analysis, and subsequent use in generating valuable reports. You will be able to understand the use of data in decision-making in companies.

Training Highlights
  • Live classes by professional trainers
  • Practice on actual data sets
  • Industry-Specific Data Analytics Training in Gurgaon
  • Working with real examples – Case Studies
  • Enhanced and job-related course material
  • Resume creation and interview preparation
  • Dedicated placement support

What You Get

  • Live instructor-led sessions with recordings
  • Practice datasets for learning
  • Real-time project experience
  • Resume and interview guidance

Course Design & Approved By

Nasscom & Wipro

What Will You Learn in Data Analytics Training

Our Data Analytics Training in Gurgaon teaches each tool step by step in a very simple manner so that even beginners can follow easily.

Core Modules Covered

  • Basics of Data Analytics
  • Excel for Data Analysis
  • SQL for working with databases
  • Data cleaning and data preparation
  • Python for data analysis
  • Statistics needed for data analysis

Advanced Topics & Projects

  • Data visualization using Power BI
  • Exploratory Data Analysis (EDA)
  • Business dashboards and reports
  • Live Data Analytics projects
  • Case studies based on real companies

Download Curriculum

Get a peek through the entire curriculum designed that ensures Placement Guidance

Course Design By

nasco wp

Course Offered By

Why Choose Our Data Analytics Training Material & Resources?

  • Training videos
  • Simple notes for every topic
  • Real business case studies
  • Practice assignments
  • Interview and certification question

Benefits of Joining Our Data Analytics Course

  • Work on real datasets
  • Lifetime access to LMS
  • Recorded videos for revision
  • Live doubt-clearing sessions
  • Certification support
  • 100% placement assistance
Learners Reviews

“Joining this course was the best decision for my career change as they not only completed the course but helped me with the interviews also.”

— Aastha, MIS Analyst

“Recorded videos helped me revise topics anytime. The support team was very supportive.”

— Ravinder, Data Analytics Consultant

“Projects were based on real business data, which gave me confidence to work in real jobs.”

— Amit, Data Visualization Analyst

“Live online classes were very helpful. All doubts were cleared properly.”

— Pooja, Reporting Analyst

“I had no technical background earlier, but the training made it easy to understand data analysis. Practice tasks helped a lot.”

— Kavita Joshi, Junior Data Scientist

“This Data Analytics Course helped me understand data concepts from the beginning. The trainer explained everything clearly and slowly.”

— Ankit, SQL & Data Visualization
Data Analytics - Country-Wise Job Profiles & Salary

Top Job Profiles:

  • Data Analyst
  • Data Scientist
  • Senior Data Scientist
  • ML Engineer

Average Salary Range:

  • INR 4 LPA - INR 8 LPA (Entry Level)
  • INR 8 LPA - INR 18 LPA (Mid Level)
  • INR 18 LPA - INR 35+ LPA (Senior)

Top Job Profiles:

  • Data Analyst
  • Data Scientist
  • Senior Data Scientist
  • ML Engineer:

Average Salary Range:

  • $70,000 - $95,000 (Entry Level)
  • $110,000 - $150,000 (Mid Level)
  • $120,000 - $170,000+ (Senior)

Top Job Profiles:

  • Data Analyst
  • Data Scientist
  • Senior Data Scientist
  • ML Engineer

Average Salary Range:

  • CAD 60,000 - CAD 85,000 (Entry Level)
  • CAD 90,000 - CAD 130,000 (Mid Level)
  • CAD 100,000 - CAD 160,000+ (Senior)

Top Job Profiles:

  • Data Analyst
  • Data Scientist
  • Senior Data Scientist
  • ML Engineer

Average Salary Range:

  • £35,000 - £50,000 (Entry Level)
  • £55,000 - £80,000 (Mid Level)
  • £80,000 - £120,000+ (Senior)

Enroll Today

Join our Data Science Course in Gurgaon with Placement support and start your career with live projects, expert trainers, and full interview help.

About the Trainer

The best thing about our courses is that you will be trained under experts having years of experience. They are industry trainers with years of practical experience in Data Science, Machine Learning, Artificial

  • Industry-certified Data Analytics professional
  • 8+ years of hands-on experience in analytics projects
  • Expertise in Excel, SQL, Power BI, Python, and Tableau
  • Delivered training to freshers and working professionals
  • Real-time project–based teaching approach
Frequently Asked Questions

You will learn Excel, SQL, Python, Statistics, Power BI/Tableau, data cleaning, and live projects.

Yes. This Data Analytics Course in Gurgaon starts from basics and is suitable for beginners.

Yes. You will get notes, recorded sessions, practice datasets, and project exercises.

Yes. We help with certification preparation and interview questions.

Data Analytics Course in Gurgaon is live. Recorded sessions are provided for revision.

CURRICULUM & PROJECTS

Data Analytics Training Program

    Introduction

    • What is Data Analytic
    • Common Terms in Data Analytics
    • What is data
    • Classication of data
    • Relevance in industry and need of the hour
    • Types of problems and business objectives in various industries
    • How leading companies are harnessing the power of analytics
    • Critical success drivers.
    • Overview of Data Analytics tools & their popularity.
    • Data Analytics Methodology & problem-solving framework.
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    Introduction To Python

    • Installation and Working with Python
    • Understanding Python variables
    • Python basic Operators
    • Understanding the Python blocks.

    Python Keyword and Identiers

    • Python Comments, Multiline Comments.
    • Python Indentation
    • Understating the concepts of Operators
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    Introduction to Statistics

    • Categorical Data
    • Numerical Data
    • Mean
    • Median
    • Mode
    • Outliers
    • Range
    • Interquartile range
    • Correlation
    • Standard Deviation
    • Variance
    • Box plot

    Understanding Statistics

    • Descriptive Statistics
    • Sample vs Population Statistics
    • Random variables
    • Probability distribution functions
    • Expected value
    • Normal distribution
    • Gaussian distribution
    • Z-score
    • Spread and Dispersion
    • Correlation and Co-variance

    Data Pre-Processing & Data Mining

    • Data Preparation
    • Feature Engineering
    • Feature Scaling
    • Datasets
    • Dimensionality Reduction
    • Anomaly Detection
    • Parameter Estimation
    • Data and Knowledge
    • Selected Applications in Data Mining

    EDA (Exploratory Data Analysis)

    • Need for structured exploratory data
    • EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)
    • Identify missing data
    • Identify outliers data
    • Imbalanced Data Techniques
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    Data Analysis and Visualization using Pandas.

    • Statistics
    • Pandas
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    SQL Server Fundamentals

    • SQL Server 2019 Installation
    • Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
    • SQL Server Features & Purpose
    • Using Management Studio (SSMS)
    • Conguration Tools & SQLCMD
    • Conventions & Collation

    SQL Server 2019 Database Design

    • SQL Database Architecture
    • Database Creation using GUI
    • Database Creation using T-SQL scripts
    • DB Design using Files and File Groups
    • File locations and Size parameters
    • Database Structure modications

    SQL Tables in MS SQL Server

    • SQL Server Database Tables
    • Table creation using T-SQL Scripts
    • Naming Conventions for Columns
    • Single Row and Multi-Row Inserts
    • Table Aliases
    • Column Aliases & Usage
    • Table creation using Schemas
    • Basic INSERT
    • UPDATE
    • DELETE
    • SELECT queries and Schemas
    • Use of WHERE, IN and BETWEEN
    • Variants of SELECT statement
    • ORDER BY
    • GROUPING
    • HAVING
    • ROWCOUNT and CUBE Functions

    Data Validation and Constraints

    • Table creation using Constraints
    • NULL and IDENTITY properties
    • UNIQUE KEY Constraint and NOT NULL
    • PRIMARY KEY Constraint & Usage
    • CHECK and DEFAULT Constraints
    • Naming Composite Primary Keys
    • Disabling Constraints & Other Options

    Views and Row Data Security

    • Benets of Views in SQL Database
    • Views on Tables and Views
    • SCHEMA BINDING and ENCRYPTION
    • Issues with Views and ALTER TABLE
    • Common System Views and Metadata
    • Common Dynamic Management views
    • Working with JOINS inside views

    Indexes and Query tuning

    • Need for Indexes & Usage
    • Indexing Table & View Columns
    • Index SCAN and SEEK
    • INCLUDED Indexes & Usage
    • Materializing Views (storage level)
    • Composite Indexed Columns & Keys
    • Indexes and Table Constraints
    • Primary Keys & Non-Clustered Indexes

    Stored Procedures and Benets

    • Why to use Stored Procedures
    • Types of Stored Procedures
    • Use of Variables and parameters
    • SCHEMABINDING and ENCRYPTION
    • INPUT and OUTPUT parameters
    • System level Stored Procedures
    • Dynamic SQL and parameterization

    System functions and Usage

    • Scalar Valued Functions
    • Types of Table Valued Functions
    • SCHEMABINDING and ENCRYPTION
    • System Functions and usage
    • Date Functions
    • Time Functions
    • String and Operational Functions
    • ROW_COUNT
    • GROUPING Functions

    Triggers, cursors, memory limitations

    • Why to use Triggers
    • DML Triggers and Performance impact
    • INSERTED and DELETED memory tables
    • Data Audit operations & Sampling
    • Database Triggers and Server Triggers
    • Bulk Operations with Triggers

    Cursors and Memory Limitations

    • Cursor declaration and Life cycle
    • STATIC
    • DYNAMIC
    • SCROLL Cursors
    • FORWARD_ONLY and LOCAL Cursors
    • KEYSET Cursors with Complex SPs

    Transactions Management

    • ACID Properties and Scope
    • EXPLICIT Transaction types
    • IMPLICIT Transactions and options
    • AUTOCOMMIT Transaction and usage

    AI Integration in SQL:

    • AI Tools:
    • Copilot in Azure Data Studio or GitHub for SQL suggestions
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    Understanding Concepts of Excel

    • Creation of Excel Sheet Data
    • Range Name, Format Painter
    • Conditional Formatting, Wrap Text, Merge & Centre
    • Sort, Filter, Advance Filter
    • Different type of Chart Creations
    • Auditing, (Trace Precedents, Trace Dependents)Print Area
    • Data Validations, Consolidate, Subtotal
    • What if Analysis (Data Table, Goal Seek, Scenario)
    • Solver, Freeze Panes
    • Various Simple Functions in Excel(Sum, Average, Max, Min)
    • Real Life Assignment work

    Ms Excel Advance

    • Advance Data Sorting
    • Multi-level sorting
    • Restoring data to original order after performing sorting
    • Sort by icons
    • Sort by colours
    • Lookup Functions
    • Subtotal, Multi-Level Subtotal
    • Grouping Features
    • Consolidation With Several Worksheets
    • Filter
    • Printing of Raw & Column Heading on Each Page
    • Workbook Protection and Worksheet Protection
    • Specified Range Protection in Worksheet
    • Excel Data Analysis
    • Data Table
    • Pivot Table
    • Generating MIS Report In Excel
    • Text Functions
    • Lookup & Reference Function
    • Logical Functions & Date and Time Functions
    • Database Functions
    • Statistical Functions
    • Financial Functions
    • Functions for Calculation Depreciation
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    Introduction to Power BI

    • Overview of BI concepts
    • Why we need BI
    • Introduction to SSBI
    • SSBI Tools
    • Why Power BI
    • What is Power BI
    • Building Blocks of Power BI
    • Getting started with Power BI Desktop
    • Get Power BI Tools
    • Introduction to Tools and Terminology
    • Dashboard in Minutes
    • Interacting with your Dashboards
    • Sharing Dashboards and Reports

    Power BI Desktop

    • Power BI Desktop
    • Extracting data from various sources
    • Workspaces in Power BI

    Power BI Data Transformation

    • Data Transformation
    • Query Editor
    • Connecting Power BI Desktop to our Data Sources
    • Editing Rows
    • Understanding Append Queries
    • Editing Columns
    • Replacing Values
    • Formatting Data
    • Pivoting and Unpivoting Columns
    • Splitting Columns
    • Creating a New Group for our Queries
    • Introducing the Star Schema
    • Duplicating and Referencing Queries
    • Creating the Dimension Tables
    • Entering Data Manually
    • Merging Queries
    • Finishing the Dimension Table
    • Introducing the another DimensionTable
    • Creating an Index Column
    • Duplicating Columns and Extracting Information
    • Creating Conditional Columns
    • Creating the FACT Table
    • Performing Basic Mathematical Operations
    • Improving Performance and Loading Data into the Data Model

    Modelling with Power BI

    • Introduction to Modelling
    • Modelling Data
    • Manage Data Relationship
    • Optimize Data Models
    • Cardinality and Cross Filtering
    • Default Summarization & Sort by
    • Creating Calculated Columns
    • Creating Measures & Quick Measures

    Data Analysis Expressions (DAX)

    • What is DAX
    • Data Types in DAX
    • Calculation Types
    • Syntax, Functions, Context Options
    • DAX Functions
    • Measures in DAX
    • Measures and Calculated Columns
    • ROW Context and Filter Context in DAX
    • Operators in DAX - Real-time Usage
    • Quick Measures in DAX - Auto validations
    • In-Memory Processing DAX Performance
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    Introduction to Data Preparation using Tableau Prep

    • Data Visualization
    • Business Intelligence tools
    • Introduction to Tableau
    • Tableau Architecture
    • Tableau Server Architecture
    • VizQL Fundamentals
    • Introduction to Tableau Prep
    • Tableau Prep Builder User Interface
    • Data Preparation techniques using Tableau Prep Builder tool

    Data Connection with Tableau Desktop

    • Features of Tableau Desktop
    • Connect to data from File and Database
    • Types of Connections
    • Joins and Unions
    • Data Blending
    • Tableau Desktop User Interface

    Basic Visual Analytics

    • Visual Analytics
    • Basic Charts Bar Chart, Line Chart, and Pie Chart
    • Hierarchies
    • Data Granularity
    • Highlighting
    • Sorting
    • Filtering
    • Grouping
    • Sets

    Calculations in Tableau

    • Types of Calculations
    • Built-in Functions (Number, String, Date, Logical and Aggregate)
    • Operators and Syntax Conventions
    • Table Calculations
    • Level of Detail (LOD) Calculations
    • Using R within Tableau for Calculations

    Advanced Visual Analytics

    • Parameters
    • Tool tips
    • Trend lines
    • Reference lines
    • Forecasting
    • Clustering

    Level of Detail (LOD) Expressions in Tableau

    • Count Customer by Order
    • Profit per Business Day
    • Comparative Sales
    • Profit Vs Target
    • Finding the second order date
    • Cohort Analysis

    Geographic Visualizations in Tableau

    • Introduction to Geographic Visualizations
    • Manually assigning Geographical Locations
    • Types of Maps
    • Spatial Files
    • Custom Geocoding
    • Polygon Maps
    • Web Map Services
    • Background Images

    Advanced charts in Tableau

    • Box and Whiskers Plot
    • Bullet Chart
    • Bar in Bar Chart
    • Gantt Chart
    • Waterfall Chart
    • Pareto Chart
    • Control Chart
    • Funnel Chart
    • Bump Chart
    • Step and Jump Lines
    • Word Cloud
    • Donut Chart

    Dashboards and Stories

    • Introduction to Dashboards
    • The Dashboard Interface
    • Dashboard Objects
    • Building a Dashboard
    • Dashboard Layouts and Formatting
    • Interactive Dashboards with actions
    • Designing Dashboards for devices
    • Story Points

    Get Industry Ready

    • Tableau Tips and Tricks
    • Choosing the right type of Chart
    • Format Style
    • Data Visualization best practices

    Exploring Tableau Online

    • Publishing Workbooks to Tableau Online
    • Interacting with Content on Tableau Online
    • Data Management through Tableau Catalog
    • AI-Powered features in Tableau Online (Ask Data and Explain Data)
    • Understand Scheduling
    • Managing Permissions on Tableau Online
    • Data Security with Filters in Tableau Online

    AI Integration in Tableau:

    • Ask Data: Natural Language Data Exploration
    • Explain Data: Automatic statistical insights
    • Tableau GPT (Einstein Copilot - Salesforce)
    • AI forecasting in visualizations
    • Integration with Python (TabPy) and R
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    Capstone Project

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+ More Lessons

Course Design By

naswipro

Nasscom & Wipro

Course Offered By

croma-orange

Croma Campus

Our Students' Projects
1768021951.webp
HP - HR Data Analytics (Online Project)

Scenario: Analyzing employee attrition trends across departments and roles.

Live Work:
  • Data analysis using Excel and SQL
  • Building interactive dashboards and reports

Outcome: Data-driven insights helped reduce attrition risk.

1768021774.webp
Infosys – Project Resource Utilization Analysis

Scenario: Checking how teams are using their time across projects

Live Work:
  • Sorting project and employee data in Excel
  • Using SQL to see workload and usage patterns
  • Building Power BI dashboards for team reports

Outcome: Better planning of people and less work pressure

1768021700.webp
Uber – Ride Demand Analysis

Scenario: Studying ride demand at different times and locations

Live Work:
  • Analyzing trip data by time using Python
  • Running SQL queries on ride records
  • Building simple dashboards in Power BI

Outcome: Better planning of cabs and reduced waiting time

1768021522.webp
HDFC Bank – Loan Approval Analysis

Scenario: Understanding why some loans get approved and others get rejected

Live Work:
  • Organizing customer data in Excel
  • Using SQL to study approval trends
  • Python analysis to group customers by risk

Outcome: Safer loan decisions and reduced risk

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Zomato – Restaurant Rating Analysis

Scenario: Understanding rating trends.

Live Work:
  • Data cleaning
  • Visualization
  • Business insights

Outcome: Better restaurant suggestions

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Tech Mahindra – HR Data Analysis Specialist

Scenario: Studying employee attrition

Live Work:
  • Excel and SQL analysis
  • Power BI reports

Outcome: Improved workforce planning

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Flipkart – Customer Behavior Analysis

Scenario: Understanding customer buying habits

Live Work:
  • Data preparation
  • EDA using Python
  • Visualization dashboards

Outcome: Improved customer targeting

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Amazon – Sales Performance Analyst

Scenario: Studying monthly sales performance across regions

Live Work:
  • Data cleaning using Excel and Python
  • SQL queries for analysis
  • Power BI dashboards

Outcome: Better sales tracking and planning

Recent Data Analytics Job Openings in Gurgaon
Junior Data Analyst

Company: Deloitte

Location: Gurgaon

Experience: 0–1 Year

Required Skills: Cleaning and organizing data, Excel and basic SQL

Business Data Analyst

Company: Accenture

Location: Gurgaon

Experience: 1–3 Years

Required Skills: Writing SQL queries, Python for data analysis

Data Analyst – Fresher Level

Company: Genpact

Location: Gurgaon

Experience: 0–2 Years

Required Skills: Working knowledge of Excel, Basic SQL for data work.

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Advanced Excel Training in Gurgaon

Advanced Excel Training in Gurgaon with real-time projects, dashboards, formulas, VBA, and data analysis skills.

Who Can Join Data Analytics in Gurgaon
  • Why : Suitable for those starting from zero
  • Best Modules: Excel basics, SQL basics, data cleaning, simple stats
  • Career Benefit: Helps you get entry-level Data Analyst roles
  • Why : Ideal for those planning to move into data roles
  • Best Modules: Excel, SQL, Python basics, reporting tools
  • Career Benefit: Supports career shift into analytics
  • Why : Helps IT professionals use data for decision-making
  • Best Modules: SQL, Python, data handling, Power BI/Tableau
  • Career Benefit: Opens roles in Data and BI Analytics
  • Why : Helps improve reporting and analysis skills
  • Best Modules: Advanced Excel, SQL, dashboards
  • Career Benefit: Growth into senior analytics roles
  • Why : Helps make data-based decisions
  • Best Modules: Dashboards, reporting, case studies
  • Career Benefit: Better decision-making confidence
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