Job-Oriented Training
Practical learning focused on real Data Analyst skills and industry use cases.
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Data Analytics Course
Data Analyst
Turn raw data into meaningful business insights. Our classroom Data Analytics training takes you from beginner-level concepts to practical analytics using Advanced Excel, SQL, Power BI, Statistics and Python. Students learn through instructor-led sessions, practical datasets, business case studies, dashboards and portfolio projects designed to build the skills required for entry-level analytics roles.
Level
Beginner
Duration
6 Months
Learning hours
480 hours
Total classes
160
Learning format
Classroom
Batch type
Weekday
Course language
English, Hindi
AT A GLANCE
Data Analytics Course snapshot
Practical Learning
100% Hands-on
Learn through practical exercises and real-world datasets.
Industry Projects
10+ Projects
Build portfolio-ready Data Analytics projects.
Tools Covered
Excel, SQL, Python, Power BI
Work with industry-standard analytics tools.
Placement Support
Career Assistance
Resume building, interview preparation and career guidance.
ABOUT THE COURSE
About Data Analytics Course
The Data Analytics Course is designed for students, freshers and working professionals who want to build a career in data analytics.
In this course, students will learn how to collect, clean, analyze and visualize data using industry-standard tools such as Microsoft Excel, SQL, Power BI and Python.
The course focuses on practical learning, real-world datasets, dashboards, business case studies and hands-on projects so students can develop job-ready data analytics skills.
WHY CHOOSE THIS COURSE
Why choose our Data Analytics Course ?
Hands-On Projects
Build practical experience with real-world datasets, dashboards, and analytics projects.
Complete Analytics Stack
Learn Excel, SQL, Python, Power BI, Statistics, DAX, and AI tools.
Beginner Friendly
Start from the fundamentals and gradually move toward advanced analytics concepts.
UNDERSTAND THE FIELD
What is Data Analytics?
Data Analytics is the process of collecting, cleaning, organizing, analyzing, and interpreting data to discover useful patterns, trends, and insights. It helps businesses and organizations understand what is happening, why it is happening, and what actions can be taken based on data.
A Data Analyst works with tools such as Excel, SQL, Python, Power BI, statistics, and data visualization platforms to transform raw data into meaningful reports, dashboards, and business insights. The goal is not only to work with numbers, but to use data to solve real problems and support better decision-making.
Data Analytics is widely used across industries such as finance, healthcare, e-commerce, marketing, education, manufacturing, and technology. As organizations generate more data, the ability to understand and use that data effectively has become an important business skill.
PROFESSIONAL CONTEXT
Data Analyst
A Data Analyst is a professional who works with data to help businesses understand performance, identify patterns, solve problems, and make better decisions. They collect data from different sources, clean and organize it, analyze trends, and present meaningful insights through reports, dashboards, and visualizations.
Data Analysts commonly use tools such as Excel, SQL, Python, Power BI, and statistical techniques to work with large datasets and convert raw information into clear business insights. Their role often includes creating KPIs, preparing reports, building dashboards, finding trends, and answering important business questions using data.
They work across industries such as finance, healthcare, e-commerce, marketing, education, manufacturing, and technology. A successful Data Analyst combines technical skills with analytical thinking, business understanding, problem-solving, and the ability to communicate findings clearly to both technical and non-technical teams.
CAREER BENEFITS
Why learn Data Analytics?
High Career Demand
Data analytics skills are used across industries for smarter business decisions.
Work With Real Data
Learn how to clean, analyze, and interpret practical datasets effectively.
Build Valuable Skills
Develop strong knowledge of Excel, SQL, Python, Power BI, and analytics tools.
Make Better Decisions
Understand how data helps identify trends, problems, and business opportunities.
LEARNING PATH
Step-by-Step Learning Roadmap
Follow a structured journey from fundamentals to job-ready skills.
01
1
Data Analytics Fundamentals
Understand data, analytics types, business problems, datasets and the Data Analytics lifecycle.
02
2
Advanced Excel
Learn formulas, lookup functions, Pivot Tables, charts, cleaning and reporting.
03
3
SQL & Databases
Learn SQL queries, joins, subqueries, aggregate functions, database concepts, and how to extract useful information from relational databases.
04
4
Python for Data Analysis
Build Python fundamentals and work with NumPy and Pandas for data manipulation, cleaning, transformation, and analysis.
05
5
Statistics for Analytics
Learn descriptive statistics, probability basics, distributions, correlation, regression concepts, and statistical thinking for data analysis.
06
6
Power BI & Data Visualization
Learn Power Query, data modeling, DAX, interactive dashboards, KPIs, reporting, and visual storytelling using Power BI.
07
7
Real-World Projects
Apply Excel, SQL, Python, and Power BI skills to practical datasets, business problems, dashboards, and analytical case studies.
08
8
Portfolio & Career Preparation
Build a project portfolio, improve your resume, prepare for interviews, practice common Data Analyst questions, and get ready for entry-level analytics roles
COURSE CURRICULUM
What you will study
5 modules · Explore the complete learning path below
This module introduces learners to the core concepts, tools, and practical techniques used in data analytics. It focuses on understanding data, cleaning and preparing datasets, performing analysis, creating reports and dashboards, and interpreting insights for real business decisions.
Learners will work with practical examples and hands-on exercises using tools such as Excel, SQL, Python, Pandas, Power BI, Statistics, and related analytics technologies. The module is designed to build both conceptual understanding and practical confidence, helping learners apply each topic to real-world data problems
Practical work:
Build hands-on projects and dashboards using real-world datasets to apply the concepts learned in this module.
Learn formulas, logical functions, lookup functions, data cleaning, Pivot Tables, charts, conditional formatting, dashboards, and reporting techniques in Excel.
Learn relational databases, SQL queries, filtering, sorting, joins, subqueries, aggregate functions, GROUP BY, CTEs, and window functions for data analysis.
Build a strong foundation in Python including variables, data types, conditions, loops, functions, collections, and basic programming concepts required for analytics.
Learn data manipulation, filtering, transformation, aggregation, missing-value handling, merging datasets, and practical data analysis using NumPy and Pandas.
TOOLS & TECHNOLOGIES
Tools you will work with
- execl
- python
- Nampy
- Pandas
CAPSTONE PROJECT
End-to-End Sales Analytics Dashboard
Work on a real-world business dataset and complete the full analytics workflow—from data cleaning and SQL analysis to Python-based exploration and Power BI dashboard creation. The project should demonstrate your ability to turn raw data into meaningful business insights and present them clearly.
What you will build
- Cleaned and structured dataset
- SQL queries for business analysis
- Python data analysis using Pandas
- KPI and trend analysis
- Interactive Power BI dashboard
- Sales and performance insights
WHAT YOU WILL LEARN
Learning outcomes
- Analyze raw business data and convert it into useful insights.
- Create professional dashboards, reports and visualizations.
- Query and analyze relational databases using SQL
- Use Python libraries for data cleaning and exploratory analysis.
SKILLS YOU DEVELOP
Technical and professional skills
Technical skills
Data Collection
Data Cleaning
Data Transformation
Advanced Excel
SQL
MySQL
Power BI
Power Query
DAX
Python
NumPy
Pandas
Matplotlib
Statistics
Exploratory Data Analysis
Dashboard Development
KPI Reporting
Data Visualization
Business Analytics
Database Fundamentals
Professional skills
Analytical Thinking
Problem Solving
Business Understanding
Team Collaboration
Decision Making
CAREER GUIDE
Career opportunities and future scope
What Does a Data Analyst Do?
A Data Analyst collects, cleans, organizes and analyzes data to help businesses understand performance, identify trends and make informed decisions. Data Analysts commonly work with Excel, SQL, Power BI, Python and visualization tools to transform raw information into reports, dashboards and actionable insights.
Daily Work of a Data Analyst
Collect data from different sources Clean incomplete or incorrect data Write SQL queries Analyze sales, marketing, finance or operational data Create Excel reports Build Power BI dashboards Track KPIs Identify trends and patterns Present insights to managers Automate repetitive reporting tasks
JOB OPPORTUNITIES
Roles you can target
Data Analyst
₹3.5 LPA – ₹6 LPA
Power BI Developer
₹4 LPA – ₹9 LPA
Data Visualization Analyst
₹4 LPA – ₹9 LPA
Product Analyst
₹5 LPA – ₹12 LPA
CAREER GROWTH
Career progression
Advanced Excel
Learn data cleaning, formulas, Pivot Tables, dashboards, Power Query, charts, lookup functions, automation, and business reporting.
Statistics for Data Analytics
Understand mean, median, probability, variance, standard deviation, correlation, distributions, hypothesis testing, and business statistics.
INDUSTRY FIT
Where these skills can take you
Industries
Information Technology
E-commerce
Finance
Related careers
Business Analyst
Business Intelligence Analyst
Power BI Developer
Data Scientist
Product Analyst
Marketing Analyst
Financial Analyst
Operations Analyst
MIS Executive
Analytics Consultant
Data Engineer
CAREER SUPPORT
Placement and classroom support
Resume Building
Create a professional resume tailored for Data Analyst and related job roles.
Interview Preparation
Practice common technical, HR, SQL, Excel, Power BI, and project-based interview questions.
Mock Interviews
Improve confidence and interview performance through guided mock interview sessions.
Job Application Support
Get guidance on finding relevant opportunities and applying for suitable analytics roles.
Why classroom training works
- Face-to-face trainer interaction
- Live practical demonstrations
- Immediate doubt resolution
- Structured learning schedule
- Classroom assignments
- Practical lab sessions
- Trainer-guided projects
- Interview preparation
- Portfolio guidance
- Regular assessments
- Career guidance
WHO SHOULD JOIN
Is this course right for you?
This Data Analyst course is designed for students, fresh graduates, working professionals, career switchers, and anyone who wants to build a career in data analytics. It is suitable for learners from both technical and non-technical backgrounds who want to understand how data is collected, cleaned, analyzed, visualized, and used for business decision-making.
The course is especially useful for those who want to learn practical skills in Excel, SQL, Python, Power BI, statistics, data visualization, and AI-powered analytics tools. It is also a good fit for professionals who want to upgrade their current skills, move into an analytics role, or strengthen their ability to work with reports, dashboards, and real-world datasets.
No advanced programming background is required to start. Basic computer knowledge, logical thinking, and an interest in working with data are enough to begin learning and gradually build job-ready Data Analyst skills.
Prerequisites / eligibility
- College Students
- Freshers
- BCA / B.Tech / B.Sc students
- Commerce students
- Working Professionals
- Beginners interested in Data Analytics
- Anyone looking to switch into a Data Analyst career
No prior programming experience is required.
COMPARE YOUR OPTIONS
ZillionSoftech vs a typical course
| Feature | ZillionSoftech | Typical Course |
|---|---|---|
| Learning Approach | Practical, job-oriented training | Mostly theory-focused learning |
| Tools Covered | Excel, SQL, Python, Power BI, Statistics, AI Tools | Limited tools or selected topics |
| Projects | Real-world projects and practical assignments | Basic exercises or fewer projects |
CAREER COMPARISON
Compare related career paths
Data Analyst
Best for: Beginners, graduates, business-focused learners
Focus: focused learners Data cleaning, reporting, dashboards, insights
Analyze business data using Excel, SQL, Python and Power BI to identify trends and support decisions.
INDUSTRY OPPORTUNITIES
Companies hiring for these skills
Deloitte
TCS
Wipro
Genpact
KPMG
Infosys
Company names are shown for career awareness only and do not imply a partnership or hiring guarantee.
DAY IN THE LIFE
A typical professional workflow
9:30 AM
Review Business Metrics
Check dashboards, KPIs, reports and important business performance changes
LEARN SMARTER
Myths and mistakes to avoid
Common myths
- Data Analytics requires advanced mathematics. Reality: Most entry-level Data Analytics work requires practical statistics, logical thinking and business understanding rather than advanced mathematics.
- Only engineering students can become Data Analysts. Reality: Professionals from commerce, management, science and other backgrounds also work successfully in analytics.
- Data Analytics and Data Science are the same. Reality: They overlap, but Data Science generally includes more advanced programming, machine learning and predictive modeling.
Beginner mistakes to avoid
- Learning tools without practicing on real datasets
- Memorizing SQL instead of solving queries
- Creating dashboards without understanding business requirements
- Ignoring statistics
INTERVIEW PREPARATION
Prepare for real interview questions
Key interview topics
Data Analytics fundamentals
Excel formulas
Types of analytics
NumPy and Pandas
Data cleaning and preprocessing
Python/Pandas practical questions
Data Analyst roles and responsibilities
BEYOND THE CLASSROOM
Included with your course
Course certificate
Placement assistance
Demo class available
Upon successful completion of the Data Analytics course, students will receive a Course Completion Certificate from Zillions of Tech.
The certificate confirms that the learner has completed practical training in areas such as Advanced Excel, SQL, Python, NumPy, Pandas, Statistics, Power BI, Power Query, DAX, Data Visualization, and AI-assisted analytics tools.
Students are expected to complete the required learning modules, practical assignments, and projects before certification.
The certificate can be added to a resume, LinkedIn profile, and professional portfolio to showcase the skills developed during the program.
Note: This is a course completion certificate issued by Zillions of Tech and does not imply certification or endorsement by Microsoft, Google, or any other third-party organization unless explicitly stated.
COURSE GUIDE
Download the complete syllabus
Review the complete course structure, modules and learning journey.
Download SyllabusFAQ
Frequently asked questions
Data Analytics is the process of collecting, cleaning, transforming and analyzing data to identify useful information, trends and insights that support better decisions.
Yes. The course starts from fundamental concepts and gradually progresses to Excel, SQL, Power BI, Python, statistics and practical projects.
No advanced coding knowledge is required. The course starts from the basics and gradually covers practical concepts in Python, SQL, Excel, Power BI, and other analytics tools
You will learn Advanced Excel, SQL, Python, NumPy, Pandas, Statistics, Power BI, Power Query, DAX, data visualization, dashboard development, and AI tools used in data analytics.
Yes. The course is designed to take learners from beginner-level concepts to practical, job-oriented Data Analyst skills.
TAKE THE NEXT STEP
Start Your Data Analytics Career Today
Build job-ready skills in Excel, SQL, Python, Power BI, and real-world data analysis with practical training, industry projects, and career support.