4.8 (17,600) reviews 110,000
55,451*
NO COST EMI : 9,242 p.m for 6 Months
*Offer valid till 6th July 2025
Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom Training
The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
MODULE 1: DATA ANALYSIS FOUNDATION
• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain
MODULE 2: CLASSIFICATION OF ANALYTICS
• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics
MODULE 3: CRIP-DM Model
• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
• Modeling, Evaluation, Deploying,Monitoring
MODULE 4: UNIVARIATE DATA ANALYSIS
• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.
MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS
• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot
MODULE 6: BI-VARIATE DATA ANALYSIS
• Scatter Plots
• Regression Analysis
• Correlation Coefficients
MODULE 1: PYTHON BASICS
• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
MODULE 2: PYTHON CONTROL STATEMENTS
• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements
MODULE 3: PYTHON DATA STRUCTURES
• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods
MODULE 4: PYTHON FUNCTIONS
• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions
MODULE 1 : OVERVIEW OF STATISTICS
MODULE 2 : HARNESSING DATA
MODULE 3 : EXPLORATORY DATA ANALYSIS
MODULE 4 : HYPOTHESIS TESTING
MODULE 1: COMPARISION AND CORRELATION ANALYSIS
• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis
MODULE 2: VARIANCE AND FREQUENCY ANALYSIS
• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis
MODULE 3: RANKING ANALYSIS
• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis
MODULE 4: BREAK EVEN ANALYSIS
• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis
MODULE 6: Time Series and Trend Analysis
• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis
MODULE 7: DATA ANALYSIS BUSINESS REPORTING
• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
MODULE 1: DATA ANALYTICS FOUNDATION
• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity
MODULE 2: OPTIMIZATION MODELS
• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel
MODULE 4: DECISION MODELING
• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer
MODULE 1: MACHINE LEARNING INTRODUCTION
• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised
MODULE 2: ML ALGO: LINEAR REGRESSSION
• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool
MODULE 3: ML ALGO: LOGISTIC REGRESSION
• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool
MODULE 4: ML ALGO: KNN
• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool
MODULE 5: ML ALGO: K MEANS CLUSTERING
• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering
MODULE 6: ML ALGO: DECISION TREE
• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool
MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool
MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)
• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool
MODULE 1: DATABASE INTRODUCTION
• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)
MODULE 2: SQL BASICS
• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation
MODULE 3: DATA TYPES AND CONSTRAINTS
• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment
MODULE 4: DATABASES AND TABLES (MySQL)
• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table
MODULE 5: SQL JOINS
• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank
MODULE 6: SQL COMMANDS AND CLAUSES
• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries
MODULE 7: DOCUMENT DB/NO-SQL DB
• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management
MODULE 1: BIG DATA INTRODUCTION
• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction
MODULE 2: HDFS AND MAP REDUCE
• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
MODULE 3: PYSPARK FOUNDATION
• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs
MODULE 4: SPARK SQL and HADOOP HIVE
• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
MODULE 1: TABLEAU FUNDAMENTALS
• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies
MODULE 2: POWER-BI BASICS
• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION
MODULE 3: DATA TRANSFORMATION TECHNIQUES
• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values
MODULE 4: CONNECTING TO VARIOUS DATA SOURCES
• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model
After completing the course, you can pursue roles like Data Analyst, Business Analyst, HR Analyst, Data Engineer, BI Analyst, or Market Research Analyst across diverse industries.
Chennai's growing IT and analytics industry offers excellent opportunities, making it an ideal location for hands-on learning, internships, and placements. According to Deloitte, manufacturers who have embraced industrial metaverse solutions early have experienced a 12% boost in key performance indicators such as sales productivity, product quality, output, and workforce efficiency.
The Data Analyst Course typically spans 4 to 6 months, depending on the learning mode—full-time, part-time, or weekend batches, with flexible scheduling options.
The Data Analyst Course fees in Chennai ranges from ₹20,000 to ₹2,50,000, depending on the institute, mode of training, and certification inclusions.
Choose top institutes for data analyst course that offer globally recognized certifications like IABAC and NASSCOM FutureSkills, experienced trainers, internship opportunities, hands-on experience through live projects, strong placement support, and positive student feedback.
Demand for data analyst is high due to Chennai’s strong presence in IT, finance, and manufacturing sectors, which increasingly rely on data for decision-making, boosting analyst roles.
According to Glassdoor, Entry-level data analysts in Chennai typically earn an average salary of around ₹6.3 LPA. With gained experience and advanced skills, professionals can earn between ₹12 to ₹15 LPA or more, especially when working with top companies like Infosys, Accenture, Cognizant, and major startups.
Yes, many institutes offer offline data analyst training in Chennai at convenient locations in Anna Nagar, Vadapalani, and Perungudi. The area hosts several reputed institutes providing offline training with practical learning, expert guidance, and strong placement support.
Graduates from any stream, working professionals, or career switchers with a basic understanding of math and interest in data can apply at the Guindy branch.
Key data analyst tools include Excel for basic and advance analysis, SQL for querying databases, Python and R for advanced analytics, and Tableau or Power BI for visualization. Data cleaning libraries like Pandas are also essential for preparing accurate datasets.
A Data Analyst can apply for various roles including Business Analyst, Data Research Analyst, BI Analyst, Marketing Analyst, Reporting Analyst, and Junior Data Scientist, depending on their skills, experience, and domain expertise.
Yes, the course is beginner-friendly and suitable for students from non-technical backgrounds. With structured training, hands-on practice, and the right mentorship, anyone can build a successful career in data analytics.
SQL is essential for querying databases, extracting relevant data, and managing structured datasets—making it a foundational skill for data analysts.
A typical Data Analyst course covers Excel, SQL, Python, data visualization tools like Power BI or Tableau, statistics, data cleaning, exploratory data analysis, and real-world projects. It also includes career guidance, mock interviews, and placement support.
A Data Analyst course trains you in analyzing data to derive insights using tools like Excel, SQL, and Python, preparing you for analytics roles.
The scope is vast with rising data use across sectors like IT, healthcare, e-commerce, and banking—ensuring steady job demand and growth. As per a report by MarketsandMarkets, the global data analytics market is projected to grow at a CAGR of 29.9%, reaching a value of USD 655 billion by the year 2029.
Key technical skills for a Data Analyst include proficiency in Excel, SQL, Python or R, statistics, data visualization tools (like Power BI or Tableau), data cleaning techniques, and strong analytical and problem-solving capabilities.
Yes, data analyst certifications are crucial to becoming a Data Analyst in Chennai, as they validate your expertise, boost your professional credibility, and increase your chances of landing top roles. They showcase your proficiency in analytics tools and techniques, helping you stand out in a competitive Chennai job market
Top IT Companies in Chennai include TCS, Infosys, Cognizant, Accenture, Zoho, Freshworks, Wipro, and various startups and analytics firms in Chennai.
Data Analysts work on projects involving sales forecasting, customer segmentation, market trend analysis, performance reporting, and dashboard development.
Yes, Excel remains essential for tasks like data entry, cleaning, analysis, and dashboards. It’s especially useful in entry and mid-level data roles and continues to be widely used across industries for its simplicity and versatility.
While not always mandatory, having basic knowledge of Python or R is highly beneficial. Many analytical tasks can be handled with Excel and SQL, but programming enhances efficiency and opens doors to advanced analytics roles.
Data Analytics focuses on examining current data to find actionable insights, while Data Science uses complex models, machine learning, and algorithms to predict future outcomes and solve broader, more technical problems.
With companies becoming increasingly data-driven, Data Analyst course provide in-demand skills in analysis, visualization, and reporting—making them highly relevant to current job trends and boosting employment opportunities.
Yes, many data analyst institutes offer part-time and weekend classes, ideal for working professionals or students who wish to upskill without disrupting their current schedules or full-time commitments.
DataMites is highly rated for its IABAC® and NASSCOM-accredited certifications, expert mentors, real-world projects, internship support, placement assistance, and flexible learning options, making it a top choice for aspiring data analysts in Chennai.
Yes, DataMites includes internship opportunities with its Certified Data Analyst Course in Chennai, allowing learners to gain hands-on experience by working on real-time datasets and practical industry projects that boost confidence and job readiness.
Yes, DataMites provides flexible EMI payment options for learners enrolling in the Certified Data Analyst Course in Chennai, helping them manage fees with zero-cost EMI plans and monthly installment options through partnered financial services.
DataMites has a transparent refund policy. If a student cancels within the trial period or before a specific number of sessions, a partial or full refund may be issued as per the terms and conditions. Refund requests are handled promptly.
The Certified Data Analyst Course in Chennai at DataMites is priced between INR 30,000 and INR 70,000, depending on the mode of learning (online/offline), course duration, and offers available. EMI and discounts may also apply for eligible students.
Yes, DataMites provides data analyst course with placement in Chennai through its PAT (Placement Assistance Team), offering mock interviews, resume guidance, job referrals, and company tie-ups to help students secure data analyst roles confidently.
DataMites provides study materials like courseware PDFs, video lectures, toolkits, project datasets, recorded sessions, case studies, interview questions, and practice tests to support learners throughout their Data Analyst training journey.
DataMites has a well-established training center in Guindy, Vadapalani, and Anna Nagar, known for its proximity to IT parks and MNCs. It offers both online and offline learning options and is conveniently accessible via public and private transport routes.
1. Anna Nagar: A.J. COMPLEX, 1/1, Anna Arch Rd, AG Block, River View Colony, Anna Nagar, Chennai, Tamil Nadu 600040
2. Guindy: Door No. SP, Spero Primus, Primus Building, Awfis, 7A, Guindy Industrial Estate, SIDCO Industrial Estate, Guindy, Chennai, Tamil Nadu 600032.
3. Vadapalani: A.J. COMPLEX, 1/1, Anna Arch Rd, AG Block, River View Colony, Anna Nagar, Chennai, Tamil Nadu 600040
The instructors at DataMites are experienced industry professionals with rich backgrounds in analytics. They offer practical insights, personalized mentoring, and hands-on training in tools like Python, Excel, Tableau, Power BI, and SQL.
Yes, learners at DataMites in Chennai work on live client projects and real-time datasets as part of the Certified Data Analyst Course, enhancing practical exposure and making them job-ready through industry-relevant assignments and simulations.
The Certified Data Analyst Course at DataMites typically spans 6 months, depending on the selected batch (weekend or weekday), mode of learning (online or offline), and project or internship involvement during the program duration.
Yes, if you miss a class in the DataMites Certified Data Analyst Course, you will receive access to the recorded sessions. These recordings ensure that you can revisit the missed content at your convenience, helping you stay on track with the curriculum.
Yes, DataMites offers free demo classes so that learners can assess the quality of instruction, course structure, and trainer expertise before committing to the Certified Data Analyst Course in Chennai. Booking is available on their website.
DataMites has three training centers in Chennai: Guindy, Vadapalani, and Anna Nagar. These locations provide convenient offline learning options, modern classroom facilities, and expert faculty support for aspiring data analysts in the city.
DataMites accepts multiple payment options including credit/debit cards, net banking, UPI, EMI options, and payments through mobile wallets. Learners can choose their preferred method and opt for installment plans if needed during enrollment.
Yes, DataMites offers flexible learning. Students can switch between offline and online modes during the course if needed, depending on availability and batch scheduling. This ensures uninterrupted learning as per personal convenience.
To enroll, visit the official DataMites website, select the Data Analyst Course for Chennai, choose a batch, fill in your details, and make the payment. You can also contact their support team for enrollment assistance or walk-in registration.
Upon completion, you receive dual certifications—an international IABAC® certification and NASSCOM FutureSkills Foundation endorsement. These certificates validate your data analytics skills and increase your credibility in the job market.
You’ll gain skills in Excel, SQL, Python, statistics, data cleaning, data visualization (Tableau & Power BI), business analytics, problem-solving, and storytelling with data—making you ready for real-world data analyst roles.
DataMites Flexi Pass gives you 365-day access to course materials, recorded sessions, and the option to attend any session from multiple batches. It ensures you can revise or learn at your own pace and convenience without time restrictions.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
Refer & Earn
+1-628-228-6062 
