Data Analytics Course in Chennai

1876 Ratings

Build a successful career in data analytics with Edubrights' Data Analytics Course in Chennai. Designed for students, freshers, job seekers, and working professionals, this program helps you develop practical skills in data analysis, dashboard creation, business intelligence, reporting, and data visualization through hands-on learning.

Gain real-world experience by working on industry projects, business case studies, and analytics dashboards while learning how organizations use data to make informed business decisions and improve performance.

Key Highlights:

✅ Real-Time Data Analytics Projects & Business Case Studies

✅ Hands-On Dashboard Development & Data Visualization Training

✅ Industry-Oriented Analytics Curriculum

✅ Expert-Led Training with Practical Learning Approach

✅ Certification Guidance & Career Support

✅ Resume Building & Mock Interview Preparation

✅ Placement Assistance for Freshers & Professionals

✅ Flexible Online, Classroom & Weekend Training Options

Start your analytics journey with Edubrights and gain the practical skills needed to become a job-ready Data Analytics professional.

Call Course Advisor

₹25000

₹36000

Data Analytics Course in Chennai thumbnail

Enroll Now View Syllabus

Placement Assurance

100%

Case Studies and Projects

Hours of Training

20+

Expert Support

Yes

Mock Interview Preparation

100%

Certification

Yes

Skill Level

All

Language

All

Course Objectives

1. What are production data pipelines in Databricks?

Answer: Production data pipelines are automated workflows that extract, transform, and load data reliably at scale using Databricks tools like Spark, Delta Lake, and Jobs.

2. What is Medallion Architecture?

Answer: It is a data design pattern that organizes data into Bronze (raw), Silver (cleaned), and Gold (business-ready) layers for better data management and performance.

3. Who can learn Data Analytics?

Answer: Freshers, graduates, working professionals, business analysts, finance professionals, and anyone interested in data-driven careers can learn Data Analytics.

4. Is coding required for Data Analytics?

Answer: Basic SQL is essential, while Python is helpful for advanced analytics. Many beginner-level tasks can be performed using Excel and Power BI.

5. What jobs can I get after learning Data Analytics?

Answer: You can work as a Data Analyst, Business Analyst, Reporting Analyst, BI Analyst, Operations Analyst, or Junior Data Scientist.

Popular Techniques Covered in This Course

SQL (Structured Query Language)

Programming Languages: Python and R

Data Visualization Tools

Data Cleaning and Preparation

Advanced Excel Skills

Advanced SQL and Database Management

Data Transformation Engineering (dbt)

Predictive Asset Modeling

Data Storytelling & Reporting

Cloud Data Warehousing Foundations

Get Hands-on Knowledge about Real-Time Projects

Project 1

Project 1: Real-Time E-Commerce Data Pipeline

Build a production-grade pipeline to process live shopping data, customer clicks, and transactions for analytics dashboards.

Project 2

Project 2: Fraud Detection Streaming System

Design a real-time pipeline to detect fraudulent banking transactions using streaming data and anomaly detection logic.

Project 3

Project 3: End-to-End Retail Data Lakehouse

Implement Bronze-Silver-Gold architecture for retail sales, inventory, and customer analytics.

Project 4

Project 4: IoT Sensor Data Processing Pipeline

Process continuous IoT sensor data streams for predictive maintenance and system monitoring.

Project 5

Project 5: Healthcare Real-Time Analytics Platform

Build a secure pipeline to process patient data streams for real-time health insights and reporting.

Key Features

Edubrights offers Data Analyst Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: Introduction to Data Analytics

What is Data Analytics: Concepts, Types & Scope
Structured vs. Unstructured Data
Data Collection Methods and Sources
Career Roles: Analyst, BI Analyst, Data Engineer
Data-Driven Decision Making in Business

Module 2: Statistics & Probability for Analysts

Descriptive Statistics: Mean, Median, Mode, Standard Deviation
Probability Basics and Distributions
Hypothesis Testing and Confidence Intervals
Correlation and Regression Fundamentals
A/B Testing for Business Decisions

Module 3: Excel for Data Analysis

Core Formulas, Functions, Filtering & Sorting
Pivot Tables and Pivot Charts
Data Cleaning and Preprocessing in Excel
Power Query for Data Transformation
Building Dynamic Dashboards and Reports

Module 4: SQL & Database Management

Relational Databases: Tables, Keys, Schemas
Core Queries: SELECT, INSERT, UPDATE, DELETE
Joins, Subqueries and CTEs
Aggregations, Window Functions & GROUP BY
Query Optimization and Indexing Basics

Module 5: Python for Data Analysis

Python Basics: Variables, Loops, Functions
NumPy and Pandas for Data Manipulation
Data Cleaning, Wrangling and Preprocessing
Exploratory Data Analysis (EDA)
Matplotlib and Seaborn for Visualization

Module 6: Power BI & Data Visualization

Power BI Interface: Reports, Data & Model Views
Connecting and Transforming Data (Power Query)
DAX Fundamentals: Measures and Calculated Columns
Building Interactive Dashboards and Visuals
Publishing, Sharing and Collaboration in Power BI

Module 7: Advanced SQL & Python

Advanced SQL: Stored Procedures, Views, Triggers
Connecting Python to SQL Databases
Automating Data Workflows with Python
Statistical Analysis with SciPy and Statsmodels
Building End-to-End Analysis Pipelines

Module 8: Data Storytelling & Reporting

Principles of Effective Data Visualization
Choosing the Right Chart for the Right Data
Structuring Business Reports and Presentations
Dashboards for Stakeholders and Executives
Communicating Insights Clearly and Concisely

Module 9: Intro to Machine Learning for Analysts

What Analysts Need to Know About ML
Linear and Logistic Regression with Python
Clustering for Customer Segmentation
Basic Time Series Analysis and Forecasting
Model Evaluation and Interpreting Results

Module 10: Capstone Projects & Portfolio

End-to-End Real-World Business Projects
Sales, Marketing and Operations Case Studies
Building a GitHub / Portfolio of Work
Interview Prep: SQL Challenges and Case Studies
Resume, LinkedIn and Job Application Guidance

Receive Training From Our Skilled and Effective Trainers

Experience in the Industry Gain knowledge from experts with practical Data Analyst project experience in a variety of sectors.

Backgrounds at the Top Prominent corporations such as hcl, tcs , accenture and cognizant employ trainers.

Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.

Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.

Up-to-Date Knowledge Trainers stay current with the latest tools, techniques and best practices.

Databricks Advanced Data Engineering – Production Pipelines Certification

Our institution offers a recognized Data Analytics certification. This certification enhances your portfolio and prepares you for collaborative projects in real-world environments. Gain practical skills through hands-on training and assessments.

Course FAQs

1. What does a Data Analyst do?

A Data Analyst collects, processes, and performs statistical analyses on large datasets to help businesses make data-driven decisions. They interpret data trends and communicate insights to stakeholders.

2. What are the key skills required for a Data Analyst?

Important skills include proficiency in SQL, Excel, Python or R for data manipulation, knowledge of statistics and probability, data visualization tools like Tableau or Power BI, and strong communication skills.

3. What types of data do Data Analysts work with?

They work with structured data (organized in databases) and unstructured data (like text, images, or social media data), depending on the project requirements.

4. How do Data Analysts handle missing or incomplete data?

They use techniques such as data imputation, removing incomplete records, or applying statistical methods to estimate missing values, ensuring data quality for analysis.

5. What is the difference between correlation and causation?

Correlation indicates a relationship or pattern between two variables, while causation implies that one variable directly affects the other. Analysts must be careful not to infer causation solely from correlation.

6. How do Data Analysts communicate complex findings to non-technical stakeholders?

They use clear storytelling, visualizations, and simplified explanations to translate technical results into actionable business insights.

7. What tools are commonly used by Data Analysts?

Common tools include SQL for database querying, Excel for data manipulation, Python and R for analysis and visualization, and BI tools like Tableau and Power BI for dashboards.

8. How do Data Analysts ensure the accuracy and integrity of their data?

By performing data cleaning, validation, cross-checking with multiple sources, and using automated scripts to detect anomalies or errors.

9. What is data cleaning?

Data cleaning involves identifying and correcting errors, removing duplicates, handling missing values, and ensuring consistency in datasets before analysis.

10. How do Data Analysts prioritize tasks when handling multiple projects?

They manage time efficiently using project management tools, prioritize based on business impact and deadlines, and communicate clearly with stakeholders about progress.

11. What is the fee for the Data Analytics Course in Chennai at EduBrights?

The Data Analytics Course fee at EduBrights, Chennai is ₹19,800 after the current 20% discount (original price ₹26,000). This fee includes training, study materials, certification, and placement support. Easy EMI options are also available. Call +91 94980 46428 for the latest batch details and offers.

12. How long is the Data Analytics Course in Chennai?

The Data Analytics Course at EduBrights, Shenoy Nagar, Chennai typically takes 2 to 3 months (around 40 hours of training). Fast-track batches can be completed in as little as 6 weeks. Weekend batches are also available for working professionals.

13. Is online Data Analytics training available at EduBrights?

Yes, EduBrights provides live online Data Analytics training across India. All sessions are instructor-led (not just recorded videos) and follow the same curriculum as classroom training. Both weekday and weekend batches are available.

14. What tools and technologies are covered in the Data Analytics Course?

The course covers Advanced Microsoft Excel, SQL, Python (Pandas, NumPy, Matplotlib, Seaborn), Power BI, Tableau, Statistics & Probability, and introductory Machine Learning concepts. Students also work on real-time projects and datasets.

15. Is this Data Analytics Course suitable for freshers with no experience?

Yes, this course is designed for beginners as well as professionals. It starts with the basics of Excel and statistics and gradually covers Python, SQL, Power BI, and Tableau. No prior coding knowledge is required.