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Data Analytics Online Course

Data Analytics Online Course with 100% Placement Support

Nowadays, data surrounds us all the time. Each business entity, whether it be a small enterprise or a huge organization, applies data to analyze its clients, upgrade services & make sound business decisions. A Data Analysis Course in India is aimed at teaching you all.

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

Data Analytics Course Demo Videos

You can attend a demo session of our Data Analytics Course before enrolling. Demo helps you understand how live classes are conducted.

Our Recently Data Analyst Course Placed Students

Riya Malhotra

Placed at Cognizant

Amit Joshi

Placed at IBM

Neha

Placed at Deloitte

Kunal Patil

Placed at Capgemini

Pooja

Placed at Accenture

Rohit

Placed at Wipro

Sneha Kulkarni

Placed at Infosys

Aarav Mehta

Placed at TCS

Data Analytics Online Course Videos

About the Data Analyst Online Course

Our Data Analyst Online Course in India is tailored to students, freshers, job aspirants, and working professionals who wish to develop themselves in the field of data analytics from scratch. This practical Data Analytics Training in India concentrates on learning real-life skills which are required to be possessed by an aspiring Data Analyst. You will be trained in handling data, reporting, dashboarding, and deriving relevant insights which will contribute to organizational growth. This program ensures practical learning through projects and other activities guided by professional trainers.

Training Highlights
  • Up-to-date training materials according to current industry trends
  • Live interactive online sessions with skilled trainers
  • Hands-on learning using real-world data sets
  • Project-based training and assignments
  • Skills training in Excel, SQL, Power BI, Tableau, Python
  • Dashboarding & reporting hands-on experience
  • Support to prepare resume

What You Get

  • Live Instructor Led Classes
  • Recorded Lectures for Revision
  • Practical assignments
  • Sessions for Clarifying Doubts
  • Help in Creating Resume
  • Assistance in Preparing for Interview
  • Case Studies from Industry
  • Assistance in Certification

Course Design & Approved By

Nasscom & Wipro

What Do You Learn in a Data Analyst Course?

This Data Analyst Online Course offers insights into how data analytics are used in the real world of businesses. Data Analytics Online Course teaches skills in organizing data, reporting, trend analysis, and presenting data in a comprehensible manner.

Core Modules Covered

  • Introduction to Data Analytics
  • Business Data Analytics
  • Advanced Excel for Data Analytics
  • SQL for Data Management
  • Data Cleaning
  • Tableau Dashboards
  • Concepts of Business Reporting

Advanced Topics & Projects

  • Basics of Statistical Analysis
  • Data Pattern & Trend Recognition
  • Interactive Dashboard Building
  • AI Assisted Analytics Tools
  • Automated Reporting Solutions
  • Real-Time Analytics Projects
  • Placement Oriented Training

Download Curriculum

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

Course Design By

nasco wp

Course Offered By

What Makes This Data Analytics Course a Good Choice?

  • Analytics Software Training
  • Practical Project Experience
  • Useful Business Case Studies
  • Building of Dashboards
  • Data Cleaning and Reporting
  • Basics of Business Intelligence

Tools & Technologies Included in the Course

  • Advanced Excel: Learn the formulas
  • SQL: Learn database fundamentals
  • Python: Basic programming
  • Power BI: Learn how to create report
  • Tableau: Creating visual reports
  • Statistics: Statistical basics
  • NumPy: Efficiently work
Learners Reviews

“The resume and interview support after the course was very helpful.”

— Megha Shah – Junior Data Analyst

“Recorded sessions were useful for revising topics whenever I had time.”

— Deepak Verma – Operations Executive

“This course gave me the confidence to attend interviews and answer questions clearly.”

— Pallavi Joshi – Data Analyst

“Hands-on practice helped me connect theory with real work situations.”

— Vinay Nair – Working Professional

“The trainer explained each topic patiently. Even difficult parts were easy to understand.”

— Sneha – Data Analysis Student

“The training helped me see how data is actually used for everyday business decisions.”

— Rohit Malhotra – Data Analyst
Country-Wise Data Analytics Jobs & Salary Guide

Top Job Profiles:

  • Data analyst,
  • Junior Data Analyst
  • Business Analyst
  • Data Analytics Executive

Average Salary Range:

  • INR 4 LPA - INR 7 LPA for freshers
  • INR 8 LPA - INR 15 LPA with experience
  • INR 18 LPA - INR 20+ LPA for senior roles

Top Job Profiles:

  • Data Analyst
  • Senior Data Analyst
  • Business Analyst

Average Salary Range:

  • $70,000 - $90,000 per year for beginners
  • $95,000 - $125,000 per year with experience
  • $135,000 - $140,000+ per year for senior roles

Top Job Profiles:

  • Data Analyst
  • Business Analyst
  • Senior Data Analyst

Average Salary Range:

  • £40,000 - £55,000 per year for freshers
  • £60,000 - £80,000 per year with experience
  • £90,000 - £110,000+ per year for senior roles

Top Job Profiles:

  • Data Analyst
  • Business Analyst
  • Sr. Data Analyst

Average Salary Range:

  • EUR 65,000 - EUR 85,000 per year for beginners
  • EUR 75,000 - EUR 95,000 per year with experience
  • EUR 110,000 - EUR 140,000+ per year for senior roles

Enroll Today

Start your learning journey with our Data Analysis Online Training. Enroll now and build strong data analysis skills for your career.

About the Trainer

Data Analysis Online Training is provided by highly qualified instructors with proven industry experience in various sectors. The hands-on knowledge gained from practical training sessions will enable learners.

  • 10+ years of industry experience
  • Excel, SQL, Power BI, Tableau, and Python Expertise
  • Experience in Training Students and Professionals
  • Hands-on and Practical Approach
  • Examples and Case Studies from the Industry
  • Industry Project Assistance
  • Helping with Resumes
Frequently Asked Questions

Croma campus is one of the best institute for training of IT professional jobs. It is one of the most prestigious and certified organizations that has been associated with the top most MNCs. Croma campus is situated in Noida which is really famous for its innovative and technical teaching methods. So, if you want to get linked with Data Analytics then do a Collab with Croma Campus.

Data Analytics is a process of examining datasets to know about the information they contain. There are a lot of works and jobs under Data Analytics. The first thing you need to do is to always keep your profile updated on LinkedIn because they are directly associated with Data Analytics. So, if you get an Data Analytics certificate you can work as Data Analyst.

Data Analytics is nowadays becoming a very important certification that can lead you to get a good job. To get any Data Analyst job you need to get a certification in Data Analytics. There is a list of things after which you can get a certificate that contains in-depth training, many simultaneously exams, live demos, and other industrial projects that can make you a perfect Data Analyst. After all this training, you can get an Data Analytics certification.

Croma Campus India program sizes a powerful training tool that can be applied in classrooms as well as in manufacturing. We offer a wide range of agendas for Live Project Data Analytics Training in India under the leadership of the best industrial experts. We are always awarded for the past 10 years as the Best Data Analytics Online Training in India.

The ways to connect Croma Campus

  • Phone Number: - +91-120-4155255, +91-9711526942
  • Email: - info@cromacampus.com
  • Address: - G-21, Sector-03, Noida (201301)

You will be able to clean data properly, identify any errors, understand data patterns, and generate clear reports that will be helpful for company activities.

As part of this Data Analysis Online Course, you’ll actually work on real data files to correct problems, organize information, and better grasp what’s being shown in the data.

The Data Analytics Online Training also has practice problems and projects using actual business data, not just theory.

The Data Analyst Course informs learners of ways to find absent numbers and eliminate incorrect ones while ensuring that numbers are accurate before usage.

You will find out how to write simple reports to explain the results in simple terms in such a way that teams and management are able to understand.

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
1769511109.webp
IBM - Dashboard Optimization Project

Scenario: Keeping dashboards updated

Live Work:
  • Updated data regularly
  • Checked values
  • Fixed small issues
  • Kept reports current

Outcome: Dashboards always showed correct data

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HCL Tech - Sales Performance Report Project

Scenario: Making easy sales reports

Live Work:
  • Collected sales data
  • Created simple reports
  • Checked totals
  • Explained results clearly

Outcome: Managers could understand the reports

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Wipro - Risk Data Management Project

Scenario: Finding risky cases in data

Live Work:
  • Checked past records
  • Found risk signs
  • Updated results
  • Verified numbers

Outcome: Risks were easier to spot

1769510588.webp
Deloitte - Data Quality Improvement Project

Scenario: Fixing messy data

Live Work:
  • Removed duplicate entries
  • Fixed missing data
  • Arranged the data properly
  • Prepared it for use

Outcome: The data was clean and ready

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Capgemini – Product Data Analysis Project

Scenario: Understanding product data.

Live Work:
  • Studied product records
  • Compared product numbers
  • Made simple notes
  • Shared findings

Outcome: Product performance became clear.

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Accenture – Data Validation & Checking Project

Scenario: Finding mistakes in data

Live Work:
  • Checked data for errors
  • Removed wrong entries
  • Filled missing values
  • Reviewed final data

Outcome: The data became reliable.

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TCS – Customer Data Insights & Reporting

Scenario: Learning about customers from data.

Live Work:
  • Looked at customer details
  • Sorted customers into groups
  • Compared customer data
  • Fixed small data issues

Outcome: The company understood customers more clearly.

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Infosys – Sales Data Analysis & Reporting

Scenario: Understanding sales using past data.

Live Work:
  • Collected old sales records
  • Cleaned the data
  • Checked sales numbers
  • Made simple summaries

Outcome: The team could understand sales better.

Recent Data Analytics Job Requirements
Junior Data Analyst

Company: Capgemini

Location: Hyderabad

Experience: 0–2 Years

Required Skills: Managing data, SQL basics, data visualization & reports

Business Data Analyst

Company: Infosys

Location: Pune

Experience: 0–2 Years

Required Skills: Analyzing data, Excel, Power BI or Tableau, making reports

Data Analyst

Company: TCS

Location: Bangalore

Experience: 0–2 Years

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

Data Analytics Related Courses

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Advanced Excel Online Course

Get knowledge of advanced Excel tools and formulas to analyze and present reports in a professional format.

SQL Online Training

Master SQL to manage, query, and effectively analyze your data with ease in the real world.

Business Analyst Online Course

Analyze data in businesses, generate reports, make appropriate decisions, and much more with this online course.

Who Can Join Data Analytics Course?
  • Why : Good for anyone starting a career in data analytics with no prior experience.
  • Best Topics: Basics of data analytics, working with data, reports
  • Job Benefit: Can apply for junior data analyst positions
  • Why : Helpful to those who want to move to roles related to data
  • Best Topics: Data handling, analysis work, real project practice
  • Job Benefit: Ability to move into a Data Analytics job
  • Why : Suitable for individuals from non-technical fields and those willing to work with data
  • Best Topics: Basic data work, Basic analysis work, Easy practice material, Easy analysis situations
  • Job Benefit: Entry-level jobs in data team
  • Why : Helps understand the use of data in real systems.
  • Best Topics: Full data process, working with real data
  • Job Benefit: Can work better on data projects
  • Why : This helps in the understanding of the data in business decisions
  • Best Topics: Simple reports, reading of data results, trends.
  • Job Benefit: Ability to make better choices, communicate direction to teams
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