Data Analytics continues to be one of the fastest-growing career paths in 2026, with companies across industries relying on data-driven decision-making. Whether you’re a student, job seeker, or working professional looking to upskill, understanding the Data Analytics syllabus gives you a clear picture of the skills and tools you need to build a strong career.

At Arivu Skills, our Data Analytics program is built in collaboration with industry experts and hiring partners to ensure that every learner becomes job-ready with practical knowledge. This detailed syllabus breakdown will help you understand what you will learn, how the modules flow, and why this skill is so valuable today.

“Master data analytics in Bangalore and get job-ready faster. Enroll now.”

1. Introduction to Data Analytics

The journey begins with the fundamentals of analytics and how data shapes modern business decisions.

Topics covered:

• What is Data Analytics?
• Why Data Analytics is essential in 2026
• Types of analytics: Descriptive, Diagnostic, Predictive & Prescriptive
• Overview of data sources, databases, and data formats
• Real-world applications across industries
• Job roles in analytics: Data Analyst, Business Analyst, BI Analyst

At Arivu Skills, we ensure learners understand the real impact of analytics through case studies and industry examples.

2. Excel for Data Analytics (with AI-powered features)

Excel remains a core tool for analysts, and in 2026 it now includes powerful AI-driven features that boost productivity.

Syllabus includes:

• Excel basics to advanced functions
• Lookup functions: VLOOKUP, XLOOKUP, INDEX-MATCH
• Pivot tables & dashboards
• Data cleaning and preprocessing
• Forecasting techniques
• Using AI tools inside Excel for automation and insights

Arivu Skills integrates practical exercises so learners build confidence from Day 1.

3. SQL for Data Extraction & Analysis

SQL is the backbone of Data Analytics, and every analyst must be fluent in querying databases.

Topics:

• Database fundamentals
• Query writing (SELECT, UPDATE, DELETE, INSERT)
• Filtering, sorting & grouping
• Joins: INNER, OUTER, CROSS, SELF
• Subqueries & CTEs
• Window functions
• Basic query optimization
• Writing SQL for real business scenarios
  

Arivu Skills provides hands-on practice using real industry datasets.

4. Statistics & Data Interpretation

Statistics helps analysts derive meaning from data and make reliable decisions.

You’ll learn:

• Types of data
• Mean, median, mode, variance & standard deviation
• Probability and distributions
• Correlation vs causation
• Hypothesis testing
• Confidence intervals
• Basic regression analysis

This module builds the analytical thinking needed for all other sections of the course.

5. Python for Data Analytics (Optional Module)

Python adds automation, scalability, and advanced analytical abilities.

Topics covered:

• Python fundamentals
• Data analysis using Pandas & NumPy
• Data visualization with Matplotlib & Seaborn
• Data cleaning and transformations
• Working with APIs
• Basic machine learning concepts (optional)
• Real-world scripts and automation

Arivu Skills includes practice exercises, mini-projects, and guided coding sessions.

6. Data Visualization using Power BI

Power BI helps you transform raw data into interactive dashboards.

Syllabus:

• Power BI interface and data import
• Data modelling and relationships
• DAX formulas
• Charts, KPIs & custom visuals
• Designing dashboards with storytelling frameworks
• Publishing and sharing reports

Arivu Skills emphasizes real business dashboards for portfolios.

7. Tableau for Data Storytelling

Tableau is widely used for business intelligence and visual analytics.

You’ll learn:

• Connecting to various data sources
• Measures, dimensions & data types
• Calculated fields
• Filters, parameters & sets
• Dashboards & storyboards
• Industry-specific visualization techniques
  

With Arivu Skills’ guidance, your Tableau portfolio becomes interview-ready.

8. Business & Domain Knowledge

Technical skills matter, but understanding business problems makes you a true analyst.

Modules include:

• Understanding KPIs and metrics
• Retail, finance, HR, supply chain & marketing analytics
• Business case studies
• Converting business questions into analytical solutions
  

This module helps learners perform well in interviews and real projects.

9. Data Cleaning & Preprocessing

Data cleaning is the most crucial step in analytics.

Topics:

• Handling missing values
• Dealing with duplicates
• Outlier detection
• Data formatting & transformation
• Feature engineering basics
• Practical cleaning exercises on diverse datasets
  

Arivu Skills ensures learners become highly skilled at working with uncleaned data—just like in real companies.

10. Capstone Projects & Assignments

By the end of the course, you work on industry-standard projects, such as:

• Sales performance dashboard
• Customer churn prediction
• Marketing campaign insights
• HR attrition analysis
• Retail forecasting
• Financial analysis model
  

These projects strengthen your resume and portfolio for job placements.

Why Choose Arivu Skills for Data Analytics in 2026?

• Updated 2026-ready curriculum
• Hands-on tools: Excel, SQL, Power BI, Tableau & Python
• Practical case studies & industry projects
• Dedicated placement support
• Expert trainers with real-world experience
• Flexible offline + online learning options
  

Arivu Skills focuses on skill-building that actually gets you hired.

FAQs