Introduction
Every day, we generate data—when we shop online, scroll social media, or even book a cab. But have you ever wondered how companies use this data to make decisions?
That’s exactly what Data Analytics (Beginner) Training helps you understand.
Think of data like raw ingredients in a kitchen. On their own, they don’t mean much. But when you process and combine them correctly, they turn into something valuable—just like insights that help businesses grow.
This course introduces you to the world of data analytics from scratch. You’ll learn how to collect, clean, analyze, and visualize data in a simple and practical way.
Industry Demand & Job Relevance
Today, every industry—from IT and finance to healthcare and e-commerce—needs data analysts. Even small businesses use data to track performance and make decisions.
If you are coming from a web development course or frontend development course, data analytics helps you understand user behavior and improve applications.
Why Now?
- Data is becoming the backbone of every business
- Entry-level data jobs are increasing rapidly
- No coding-heavy background required to start
- Strong foundation for advanced analytics, AI, and data science
Starting early in data analytics gives you a powerful career advantage.
2. COURSE PURPOSE & FIT
Purpose / Goals
- Understand basic concepts of data analytics
- Learn how to work with data using Excel and tools
- Perform data cleaning and preparation
- Create simple dashboards and reports
- Understand business insights from data
- Build problem-solving and analytical thinking
- Get ready for entry-level data roles
- Prepare for advanced analytics learning
Who Should Enrol
- Beginners with no prior experience
- Students from any background (commerce, arts, IT)
- Working professionals switching careers
- Excel users wanting to upgrade skills
- Learners from web technologies training background
- Business owners wanting to understand data
Why Take This Course
This course is designed for absolute beginners. You’ll learn step-by-step with simple examples, real datasets, and practical exercises that make learning easy and effective.
Unique Benefit
- Beginner-friendly approach
- Real-life examples and datasets
- Hands-on practice sessions
- Easy transition to advanced analytics
Industry Use-Cases
- Sales tracking and reporting
- Customer data analysis
- Basic financial reporting
- Website performance analysis (useful for HTML CSS JavaScript course learners)
- Business decision-making
Tools & Technologies Covered
- Microsoft Excel (Basic to Intermediate)
- Power BI / Tableau (Introduction)
- Basic SQL
- Data Visualization Techniques
Certification Preparation
- Beginner-level data analytics certification guidance
- Practice assignments and quizzes
- Interview preparation basics
Curriculum
- 10 Sections
- 0 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Chapter 1: Introduction to Data AnalyticsLearning Objectives:
Understand basics of data and analytics
Modules:- What is Data? (data basics)
- Types of Data (structured vs unstructured)
- Role of Data Analyst (career overview)
- Analytics Process
0 - Chapter 2: Excel for Data AnalysisLearning Objectives:
Work with data using Excel
Modules:- Excel Basics (formulas, functions)
- Data Formatting (clean data)
- Sorting & Filtering (data organization)
- Charts & Graphs
0 - Chapter 3: Data Cleaning & PreparationLearning Objectives:
Prepare data for analysis
Modules:- Removing Errors (data cleaning)
- Handling Missing Data
- Data Formatting Techniques
- Basic Data Transformation
0 - Chapter 4: Introduction to SQLLearning Objectives:
Learn basic database queries
Modules:- What is SQL? (database basics)
- SELECT Queries (data retrieval)
- Filtering Data (WHERE clause)
- Simple Joins
0 - Chapter 5: Data Visualization BasicsLearning Objectives:
Create visual reports
Modules:- Introduction to Power BI / Tableau
- Creating Charts (bar, line, pie)
- Dashboard Basics
- Data Storytelling
0 - Chapter 6: Basic Business AnalysisLearning Objectives:
Understand insights from data
Modules:- KPIs and Metrics
- Sales Analysis
- Customer Insights
- Simple Reporting
0 - Chapter 7: Mini Projects & PracticeLearning Objectives:
Apply learning with projects
Modules:- Sales Data Project
- Customer Data Analysis
- Excel Dashboard
- Website Data Analysis (frontend development course integration)
0 - Chapter 8: Career PreparationLearning Objectives:
Prepare for entry-level jobs
Modules:- Resume Building
- Interview Basics
- Portfolio Creation
- Next Learning Path
0 - CAREER & SALARY INSIGHTS (Mumbai, India)Job Roles
- Junior Data Analyst
- Data Entry Analyst
- Reporting Analyst
- Business Support Analyst
- MIS Executive
- Data Associate
- Freshers: ₹2.5 LPA – ₹5 LPA
- Mid-Level: ₹5 LPA – ₹8 LPA
- Experienced: ₹8 LPA – ₹15+ LPA
- Increasing demand for entry-level data roles
- Companies hiring freshers with basic analytics skills
- Growing use of data in all industries
- Basic Excel and data handling skills
- Understanding of data concepts
- Good communication skills
- Willingness to learn and adapt
- Basic SQL knowledge
0 - PRACTICAL OUTCOMESTools / Tech Stack Covered:
- Excel
- SQL (Basic)
- Power BI / Tableau (Intro)
- Excel Dashboard
- Sales Data Analysis
- Customer Insights Report
- Basic Visualization Project
Create a complete beginner-level analytics report:
- Data cleaning
- Data analysis
- Visualization
- Insights presentation
- Assignments
- Practice exercises
- Mini projects
- Final project
Students will build:
- Beginner-level dashboards
- Real datasets projects
- Entry-level job portfolio
0
It is the process of analyzing data to find useful insights.
Yes, it is designed for absolute beginners.
No, basic concepts are taught from scratch.
Typically 4–8 weeks.
Excel, SQL, and basic Power BI/Tableau.
Yes, entry-level roles are available.
₹2.5–₹5 LPA as a fresher.
Yes, beginner-friendly projects are included.
Guidance is provided.
Yes, any background can join.
Yes, especially for web development course learners.
Data analysis and reporting.
A language to manage databases.
Yes, with beginner projects.
You can move to advanced data analytics.
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