Do I need programming knowledge to learn Data Analytics?

No, advanced programming knowledge is not mandatory to begin learning data analytics. Beginners can start with Excel, basic statistics, and SQL before moving into Python. Excel provides an accessible way to understand data manipulation, formulas, pivot tables, and visualization. SQL allows learners to retrieve and analyze information from databases without requiring traditional application programming skills. Python can then be introduced gradually for more advanced data cleaning, automation, statistical analysis, and visualization.

What is the difference between Data Analytics and Data Science?

Data Analytics primarily focuses on examining existing data to identify patterns, trends, relationships, and insights that support business decisions. Data analysts commonly work with Excel, SQL, Power BI, Tableau, Python, and statistical techniques to answer business questions and create reports or dashboards. Data Science is broader and may involve advanced statistics, machine learning, predictive modeling, artificial intelligence, programming, and large-scale data processing. A data scientist may develop models that predict future outcomes, while a data analyst may investigate historical performance and explain why certain results occurred.

What certification can I earn after the course?

Learners can pursue a Data Analytics Certification after completing the required training and assessment offered by their training provider or certification organization. Certification can demonstrate that a learner has studied important analytics concepts and gained practical exposure to tools such as Excel, SQL, Python, Power BI, statistics, and data visualization. However, certification should ideally be supported by hands-on projects and a portfolio because employers often evaluate practical problem-solving ability alongside credentials.

Can working professionals learn Data Analytics?

Yes, working professionals can learn data analytics through flexible training formats and structured learning schedules. Professionals from finance, sales, marketing, operations, HR, IT, and management can particularly benefit because analytical skills can complement their existing domain knowledge. For example, a finance professional can apply analytics to financial reporting, while a marketing professional can analyze campaign performance and customer behavior.

Data Analytics Training with Certification

Q: Who should join a Data Analytics Course?

A Data Analytics Course is suitable for students, graduates, working professionals, business users, software professionals, and anyone interested in developing analytical skills. Beginners can start by learning fundamental concepts such as Excel, statistics, SQL, and visualization before progressing toward Python and advanced analytics

Q: Which course is best for data analytics?

The best course for data analytics should provide practical training in the tools and concepts used in real-world analytical roles. A comprehensive Data Analytics Course should cover Excel, SQL, statistics, Python, data cleaning, exploratory data analysis, Power BI, Tableau, and data visualization. Learners should also get hands-on experience through business case studies and end-to-end projects. Beginners should choose a program that starts with fundamentals and gradually progresses toward advanced analytics.

Q: Can I learn data analysis in 3 months?

Yes, you can build a strong foundation in data analysis within three months if you follow a structured learning plan and practice consistently. During the first month, focus on Excel, basic statistics, data cleaning, and analytical concepts. The second month can focus on SQL, Python fundamentals, Pandas, and exploratory data analysis. During the third month, concentrate on Power BI, Tableau, dashboard development, and real-world projects.

Q: Is data analytics a good career?

Yes, data analytics can be a strong career option for individuals interested in technology, business, numbers, and problem-solving. Organizations across industries use data to understand customers, monitor performance, improve operations, control costs, and make informed decisions. Data analysts commonly work with tools such as Excel, SQL, Python, Power BI, and Tableau to transform raw data into useful insights. Career opportunities can exist across sectors including finance, healthcare, retail, marketing, technology, logistics, and consulting. Beginners can start by developing fundamental analytical and technical skills through a structured Data Analyst Course and then build practical experience through projects.

Q: Is a data analyst a high salary?

Data analyst salaries can be competitive, but compensation varies depending on experience, location, industry, technical skills, company size, and job responsibilities. Entry-level analysts typically begin with foundational responsibilities such as reporting, data cleaning, dashboard creation, and basic SQL analysis. As professionals gain experience and develop advanced skills in Python, SQL, Power BI, statistics, data modeling, and business intelligence, they can qualify for more specialized and senior positions. Professionals who combine technical analytics skills with strong business and communication abilities may have additional opportunities for career growth. Completing practical projects and earning a relevant Data Analytics Certification can strengthen a candidate’s profile, although certification alone does not determine salary.

Q: What tools are covered in Data Analytics Training?

Data analytics training generally covers a combination of spreadsheet, database, programming, visualization, and business intelligence tools. A comprehensive program should include Microsoft Excel for data preparation and basic analysis, SQL for querying databases, and Python for advanced data manipulation and exploratory analysis. Learners can also work with libraries such as Pandas, NumPy, Matplotlib, and Seaborn.

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CoursesData Analytics

Data Analytics

Master data analysis, visualization, SQL, Excel, Python, Power BI, and real-world business insights with our Data Analytics Course designed for students, professionals, and aspiring data analysts.

5/5(4,890 Reviews)

Level

Advanced

Duration

16 Weeks

About

Training Plan

Course Curriculum

New Batch

Projects

Certificate

Testimonials

FAQ

Interview FAQ

Placement Client

About Data Analytics

Build job-ready analytical skills with our Data Analytics Course in India, designed to help learners understand data, identify trends, create dashboards, and support business decisions. This comprehensive Data Analytics Training in India covers Excel, SQL, Python, statistics, data cleaning, exploratory data analysis, Power BI, Tableau, data visualization, and real-world projects.

The program is suitable for beginners, working professionals, and aspiring analysts looking to develop practical skills through hands-on learning. Our Data Analyst Course focuses on industry-relevant tools, analytical techniques, dashboard development, and business problem-solving. Learners also gain project experience and preparation for Data Analytics Certification, helping them demonstrate their knowledge and improve their career opportunities.

Training Plan

About trainer

Working professional who is carrying more than 10 years of industry experience.

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

e-Book

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

Video Recording

Daily Session would be recorded and shared to the candidate.

Projects

Live projects will be provided for hands-on practice.

Resume Building

Expert-guided resume building with industry-focused content support.

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

Course Overview

Introduction to Data Analytics

Understand the fundamentals of data analytics, its business applications, analytical processes, and the role of a data analyst. Learners will understand how organizations use data to identify trends, solve business problems, measure performance, and make informed decisions.

Introduction to Data Analytics

Data Analytics vs Data Science

Data Analytics vs Business Intelligence

Data Analytics Lifecycle

Role of a Data Analyst

Excel for Data Analytics

Learn Microsoft Excel as a practical analytics tool for organizing, cleaning, analyzing, and presenting business data. This module covers formulas, functions, pivot tables, charts, conditional formatting, and advanced analytical techniques.

Excel Interface & Data Management

Data Formatting

Basic & Advanced Formulas

IF, SUMIF, COUNTIF

VLOOKUP & XLOOKUP

INDEX & MATCH

Conditional Formatting

Pivot Tables

Excel Dashboards

Statistics for Data Analytics

Build a strong statistical foundation required for data analysis and business decision-making. Learners will understand descriptive statistics, probability, distributions, correlation, regression, and hypothesis testing using practical examples.

Statistics Fundamentals

Mean, Median & Mode

Range & Variance

Normal Distribution

Correlation

Regression Fundamentals

Confidence Intervals

SQL for Data Analysis

Develop practical SQL skills for extracting, filtering, transforming, and analyzing structured business data from relational databases. Learners will work with queries commonly used by professional data analysts.

SQL Fundamentals

WHERE & ORDER BY

GROUP BY & HAVING

Joins

Aggregate Functions

Subqueries

Common Table Expressions

CASE Statements

Window Functions

Python for Data Analytics

Learn Python programming specifically for data analysis. This module introduces Python fundamentals and focuses on libraries such as NumPy, Pandas, and Matplotlib for handling, analyzing, and visualizing datasets.

Python Fundamentals

Variables & Data Types

Operators

Conditional Statements

Loops

Functions

NumPy

Pandas

Data Manipulation

Python Analytics Exercises

Data Cleaning & Preprocessing

Learn how to transform raw and inconsistent datasets into reliable analytical data. Learners will identify missing values, duplicates, incorrect formats, outliers, and data-quality issues before performing analysis.

Data Quality Concepts

Missing Values

Duplicate Records

Data Type Conversion

Outlier Identification

Data Validation

Data Cleaning with Excel

Exploratory Data Analysis

Learn how to investigate datasets and discover meaningful patterns, relationships, anomalies, and trends. Exploratory Data Analysis techniques will help learners understand datasets before building dashboards or analytical models.

EDA Fundamentals

Data Profiling

Bivariate Analysis

Multivariate Analysis

Trend Analysis

Correlation Analysis

Business Question Formulation

EDA using Python

Power BI for Data Analytics

Develop practical Power BI skills for transforming data into interactive dashboards and business reports. Learners will work with data sources, Power Query, data models, DAX, visualizations, filters, and dashboard design.

Power BI Introduction

Power BI Desktop

Power Query

Data Modeling

Relationships

DAX Fundamentals

KPIs

Charts & Visualizations

Interactive Dashboards

Power BI Publishing

Tableau & Data Visualization

Learn how to communicate analytical findings through effective data visualization. This module covers Tableau fundamentals, charts, dashboards, filters, calculated fields, and visualization best practices.

Introduction to Tableau

Connecting Data

Charts

Parameters

Dashboards

Storytelling with Data

Visualization Best Practices

Tableau Dashboard Project

Business Intelligence & Analytics

Understand how data analytics supports business intelligence and organizational decision-making. Learners will explore KPIs, business metrics, reporting, performance analysis, and analytical storytelling.

Business Metrics

KPIs

Operational Analytics

Sales Analytics

Marketing Analytics

Financial Analytics

HR Analytics

Performance Reporting

Data-Driven Decision Making

Analytical Storytelling

Advanced Data Analytics

Explore advanced analytical techniques and concepts used in modern data-driven organizations. Learners will understand forecasting, regression, segmentation, predictive analytics fundamentals, and AI-assisted analytics.

Advanced Analytics Concepts

Regression Analysis

Time-Series Analysis

Customer Segmentation

Scenario Analysis

AI in Data Analytics

Automated Data Insights

Projects & Career Preparation

Apply the complete analytics workflow to practical business projects. Learners will work with real-world datasets, prepare data, perform analysis, create dashboards, communicate insights, and prepare for data analyst interviews.

End-to-End Analytics Project

Data Collection

Data Cleaning

Data Analysis

Dashboard Development

Business Insights

Analytics Presentation

Resume Preparation

Data Analytics Courses

No related courses found

Additional Program Highlights

Comprehensive study materials and resources

Professional resume building session

Master your interview skills

Real-world project demonstrations

Upcoming Batches

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Weekdays

📅 14 Aug 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekdays

📅 17 Aug 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekdays

📅 19 Aug 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekdays

📅 20 Aug 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

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Eligible Candidates for this Training

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Working Professionals

Ops/Administrators/HR

Developers

BA/QA Engineers

Cloud / Infra

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Career Opportunities

Data Analyst

Junior Data Analyst

Business Data Analyst

Business Intelligence Analyst

Reporting Analyst

Data Visualization Analyst

Marketing Data Analyst

Financial Data Analyst

Operations Data Analyst

Product Data Analyst

BI Developer

Senior Data Analyst

Data Analyst

Junior Data Analyst

Business Data Analyst

Key Projects

Industry Oriented Projects

Amazon – Amazon Sales Analytics

Scenario: Analyze sales data from Amazon India operations to identify product demand, customer buying trends, regional sales performance, and revenue opportunities.

Live Work:

Analyze sales by product and region
Build Power BI sales dashboards
Identify high performing product categories

Outcome: Improve sales insights and decisions

Zomato – Zomato Order Analytics

Scenario: Analyze Zomato order data across Delhi NCR to understand delivery trends, customer preferences, restaurant performance, and peak ordering periods.

Live Work:

Analyze orders by location and time
Track delivery performance metrics
Identify customer ordering patterns

Outcome: Improve delivery and customer experience

Vodafone – Vodafone Customer Analytics

Scenario: Analyze Vodafone customer data from Bengaluru to identify purchasing behavior, product preferences, repeat customers, and regional sales opportunities.

Live Work:

Segment customers by purchase behavior
Analyze product category performance
Create customer insights dashboards

Outcome: Increase customer retention and sales

HDFC Bank – HDFC Customer Analysis

Scenario: Analyze HDFC Bank customer data from Mumbai to understand customer segments, transaction patterns, product usage, and opportunities for better customer engagement.

Live Work:

Analyze customer transaction patterns
Segment customers using key metrics
Build banking performance dashboards

Outcome: Support better banking decisions

Placement Process

Live Class with Industry Use Cases

Interactive learning
Real-world examples
Expert guidance
Doubt resolution

Daily Assignment & Weekly Assessments

Hands-on practice
Concept reinforcement
Weekly evaluation
Timely feedback

Project Testing & Deployment

Project development
Testing practice
Deployment exposure
Portfolio creation

Interview Preparation (Mock, PD, Alumni Session)

Mock interviews
Personal development
Alumni guidance
Confidence building

Resume Building

Resume crafting
Industry-focused format
Skills highlighting
Professional presentation

Placement

Job assistance
Interview support
Career guidance
Opportunity access

Latest Hiring

No hiring posts

Recently Placed Candidates

No placements available

Latest Hiring

No hiring posts

Our Success Mantra

Commitment

Ensuring quality training every day

Fulfillment

Meeting learning goals with confidence

Accomplishment

Students achieving industry-ready expertise

Our Learner Voice

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Beyond Courses:

Additional Support We Provide

24/7 Support

LinkedIn Profile

Resume Writing

Alumni Sessions

Interview Preparation

Live Projects

What Makes TechPratham Training Different?

Feature

TechPratham Advantage

Industry Standard Institutes

Real-World Implementation

Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.

Restricted or simulation-based access that lacks real-world complexity.

Subject Matter Experts

Mentorship from certified professionals with 15+ years of global industry experience.

Generic instructors with no hands-on implementation background.

2026 Ready Curriculum

AI-driven curriculum with advanced platform integrations and real-world configurations.

Basic, outdated syllabus that misses key technical integrations.

Daily & Weekly assignments

Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.

Self-paced learning with no accountability or progress tracking.

End-to-End Lifecycle

Hands-on project testing and deployment with portfolio-ready real-world exposure.

Basic lab exercises without any deployment or testing practice.

Interview Readiness

Structured interview preparation including mock interviews, PD sessions, and alumni guidance.

Minimal support limited to a generic certificate of completion.

Placement Support

Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.

Basic career tips with no direct industry connections.

Training Support

24/7 technical doubt resolution and personalized mentoring support.

Limited mentor availability and no support after class hours.

Affordable Fees

Competitive fixed pricing with flexible payment options and transparent fee structure.

Inflated fees with hidden costs and low return on investment.

Real-World Implementation

Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.

Restricted or simulation-based access that lacks real-world complexity.

Subject Matter Experts

Mentorship from certified professionals with 15+ years of global industry experience.

Generic instructors with no hands-on implementation background.

2026 Ready Curriculum

AI-driven curriculum with advanced platform integrations and real-world configurations.

Basic, outdated syllabus that misses key technical integrations.

Daily & Weekly assignments

Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.

Self-paced learning with no accountability or progress tracking.

End-to-End Lifecycle

Hands-on project testing and deployment with portfolio-ready real-world exposure.

Basic lab exercises without any deployment or testing practice.

Interview Readiness

Structured interview preparation including mock interviews, PD sessions, and alumni guidance.

Minimal support limited to a generic certificate of completion.

Placement Support

Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.

Basic career tips with no direct industry connections.

Training Support

24/7 technical doubt resolution and personalized mentoring support.

Limited mentor availability and no support after class hours.

Affordable Fees

Competitive fixed pricing with flexible payment options and transparent fee structure.

Inflated fees with hidden costs and low return on investment.

Who should join a Data Analytics Course?

Which course is best for data analytics?

Can I learn data analysis in 3 months?

Is data analytics a good career?

Is a data analyst a high salary?

What tools are covered in Data Analytics Training?

Industry-Recognized Certification

Data Analytics Certification

News Highlights

TechPratham Introduces Hire-Train-Deploy Model to Transform HR & ERP Talent in the AI Era

TechPratham Empowering Future Professionals Through AI-Focused HR & ERP Training

Featured In

TechPratham Gains Recognition for Bridging the HR & ERP Skills Gap with Hire-Train-Deploy

TechPratham's Hire-Train-Deploy Approach Reshaping HR & ERP Careers in the AI-Driven Industry

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Data Analytics

Enquire This Course

Placement Client

About Data Analytics

Training Plan

About trainer

Decks & Updated Content

e-Book

Assignments & MCQs

Video Recording

Projects

Resume Building

Interview Preparation

Course Overview

Data Analytics Courses

Additional Program Highlights

Upcoming Batches

Eligible Candidates for this Training

Career Opportunities

Key Projects

Industry Oriented Projects

Amazon – Amazon Sales Analytics

Live Work:

Zomato – Zomato Order Analytics

Live Work:

Vodafone – Vodafone Customer Analytics

Live Work:

HDFC Bank – HDFC Customer Analysis

Live Work:

Placement Process

Live Class with Industry Use Cases

Daily Assignment & Weekly Assessments

Project Testing & Deployment

Interview Preparation (Mock, PD, Alumni Session)

Resume Building

Placement

Latest Hiring

Recently Placed Candidates

Latest Hiring

Our Success Mantra

Commitment

Fulfillment

Accomplishment

Our Learner Voice

Beyond Courses:

What Makes TechPratham Training Different?

What tools are covered in Data Analytics Training?

What is the difference between descriptive and predictive analytics?

Data Analytics Certification Details

Exam Details:

Who Should Take This Course?

Important Note:

Industry-Recognized Certification

News Highlights

Featured In

India

Head Office

India

Noida Office

India

Hyderabad Office