4.8 (19,000) reviews 110,000
55,451*
NO COST EMI : 9,242 p.m for 6 Months
*Offer valid till 28th September 2025
Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom Training
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
Enrolling at DataMites was one of the best decisions I made for my career. Coming from a freelance writing background with no prior technical experience, I was initially unsure about stepping into the field of data analytics. But DataMites made the transition smooth and achievable. I’d highly recommend them to anyone looking for a guided, industry-ready data analytics course. A true DataMites success story!
Career options include roles like Data Analyst, Business Analyst, Financial Analyst, Marketing Analyst, and Data Visualization Specialist. Advanced skills may also lead to positions in Machine Learning or Data Science
India is a booming hub for data-driven businesses with growing demand for analysts across IT, finance, healthcare, and e-commerce. A data analyst course equips learners with industry-relevant skills, ensuring strong career growth and global opportunities
The duration of a certified Data Analyst course in India typically ranges between 3 to 6 months, depending on the program structure, practical exposure, and mentorship provided. Some institutes also offer fast-track or flexible learning options
Data Analyst course fees in India range from ₹20,000 to ₹2,50,000, depending on the institute, curriculum depth, and certifications offered. Institutes with global accreditation and placement support may charge on the higher end
Choose institutes accredited by reputed bodies, offering hands-on projects, expert mentors, placement assistance, and offline and online flexibility. Reviews, alumni success stories, and industry partnerships are key factors to evaluate
The demand is rising rapidly as companies rely on data-driven decision-making. With India’s analytics market projected to grow at over 30% CAGR, skilled data analysts are sought after across IT, BFSI, healthcare, retail, and consulting sectors
Entry-level Data Analysts in India earn ₹4–6 LPA, mid-level professionals earn ₹8–12 LPA, while experienced analysts and specialists can make ₹15+ LPA. Salaries vary with industry, skillset, and location, with metros offering higher packages
Graduates from science, engineering, commerce, economics, or management backgrounds are eligible. Basic knowledge of math, statistics, and logical thinking is helpful, while institutes often train learners from non-technical fields too
Key tools include Excel, SQL, Python, R, Tableau, and Power BI. Analysts also use data visualization tools, statistical software, and cloud platforms like AWS or Google BigQuery to handle real-world datasets effectively
Start by building strong skills in Excel, SQL, and data visualization. Enroll in a certified course, work on real projects, build a portfolio, and pursue internships or entry-level roles. Networking and continuous learning ensure faster growth
Yes. Many non-technical graduates successfully transition into analytics. Courses focus on building statistical understanding, coding basics, and visualization skills, enabling non-technical learners to excel in data analyst roles
SQL is essential for querying, cleaning, and managing large databases. It helps analysts extract insights directly from structured data, making it one of the most critical skills for any aspiring or practicing data analyst.
Data Analysts focus on interpreting datasets to generate business insights, while Data Scientists build predictive models, use advanced machine learning, and work on unstructured data. Analysts explain “what happened,” scientists predict “what will happen.”
The future is promising as data analytics becomes central to every industry. With AI and automation advancing, analysts skilled in visualization, business strategy, and storytelling will remain highly valuable for decision-making roles
Yes, Excel remains vital for data cleaning, quick analysis, pivot tables, and visualization. While advanced tools exist, Excel’s accessibility and widespread use make it a must-have foundational skill for every data analyst
A Data Analyst course syllabus covers Excel, SQL, Python, statistics, data visualization, Power BI/Tableau, and real-world projects. It equips learners with technical and analytical skills to handle, interpret, and present data effectively.
The best courses for data analysts in India are those offering IABAC-accredited certifications, practical training, live projects, and placement support. Institutes like DataMites stand out for providing globally recognized programs tailored to industry demands
The scope of data analytics in India is vast, with demand rising across IT, finance, healthcare, and e-commerce. With companies relying on data for decisions, data analysts enjoy lucrative job opportunities, career growth, and stability in the digital economy
Key technical skills include Excel, SQL, Python/R, data visualization (Power BI/Tableau), statistics, and machine learning basics. Proficiency in handling large datasets and communicating insights effectively makes a strong foundation for a data analyst career
Data analysts work on projects like customer behavior analysis, sales forecasting, financial reporting, risk assessment, marketing performance, and operational efficiency. These projects involve cleaning, interpreting, and visualizing data for actionable insights
Basic programming skills in Python, R, or SQL are beneficial for data analysts, as they simplify data handling and analysis. However, beginners can start with Excel and visualization tools, gradually learning coding as they progress in their career
AI tools automate repetitive data tasks, but data analysts remain essential for interpretation, context, and strategic decision-making. Rather than replacing analysts, AI enhances their capabilities, enabling faster and deeper analysis of business data
Top IT companies hiring data analysts in India include TCS, Infosys, Wipro, Accenture, Deloitte, EY, Amazon, Flipkart, and HCL. These firms offer diverse opportunities across industries, competitive salaries, and career growth in data-driven roles
While not mandatory at the start, coding skills in Python, R, or SQL give data analysts an edge. Coding helps in handling large datasets, building models, and automating workflows, making it a valuable skill for career advancement
The IABAC-accredited certifications are considered highly valuable in India as they are globally recognized. Certifications in data analytics, SQL, Python, and visualization tools like Tableau or Power BI also boost employability and industry credibility
Yes, with dedication, one can learn the fundamentals of data analysis in 3 months through an intensive course covering Excel, SQL, Python, and visualization. However, mastering advanced skills and gaining project experience requires consistent practice
Beginners can start with projects like sales dashboard creation, customer segmentation, or analyzing public datasets. Using Excel, Python, or Power BI, they can practice cleaning, analyzing, and visualizing data to build strong portfolios
Courses that combine theory, hands-on tools, live projects, and industry certifications are best. Programs from top data analyst institutes, accredited by IABAC, are designed to provide end-to-end skills needed to start a data analyst career successfully
The best data analyst institute offers global certifications, expert mentors, projects, and placement assistance. DataMites is a top choice, providing IABAC-accredited training in offline and online, making it ideal for aspiring data analysts
Yes, you can pursue a Data Analyst course on a part-time basis. Several Institutes offer flexible learning modes, including weekend and evening classes, self-paced learning, and blended options to suit working professionals and students.
After completing a data analyst course, career options include Data Analyst, Business Analyst, Data Visualization Specialist, Financial Analyst, and Marketing Analyst, with opportunities across IT, finance, healthcare, and e-commerce sectors.
DataMites is a top choice for its IABAC-accredited curriculum, expert mentors, practical projects, internships, and placement assistance. With flexible learning modes and offline centres across major cities, it offers industry-relevant, career-focused training
Yes, DataMites offers internships as part of the Certified Data Analyst course in India with internships. Internships provide learners with real-world exposure, hands-on project experience, and industry practices that help them apply concepts effectively and boost their employability
Yes, DataMites provides EMI options to make learning more affordable. Students can choose flexible payment plans that allow them to pursue the Certified Data Analyst course without financial stress, making high-quality training accessible to everyone.
The Certified Data Analyst course fees at DataMites in India varies based on course mode and offers. Typically, it ranges between ?40,000 to ?60,000 with discounts and EMI options available, ensuring cost-effective learning with quality training and support.
Yes, DataMites offers a Certified Data Analyst course in India with placements. With tie-ups across industries, students get access to job opportunities, resume building, interview preparation, and career support for a strong start in the analytics domain.
DataMites has a defined refund policy. Learners can request cancellations within the stipulated time frame, subject to terms and conditions. Refund eligibility may vary by course type and enrollment mode, ensuring transparency and flexibility for students.
The Certified Data Analyst course at DataMites typically lasts 6 months, including training, projects, and internship opportunities. The flexible learning schedule allows students to balance their coursework with practical exposure and industry readiness
DataMites has multiple offline training centers across India, located in cities like Bangalore, Pune, Hyderabad, Chennai, Coimbatore, Mumbai, Delhi, Ahmedabad, Chandigarh and Bhubaneswar. These centers provide classroom learning with expert guidance and practical exposure.
DataMites Institute has three training centers in Bangalore: Marathahalli, Kudlu Gate, and BTM Layout:
Marathahalli: 1st Floor, 761/1, Outer Ring Rd, near KLM Mall, Marathahalli Village, Marathahalli, Bengaluru, Karnataka 560037
Kudlu Gate: Bajrang House, 7th Mile, C-25, Bengaluru - Chennai Hwy, Kudlu Gate, Garvebhavi Palya, Bengaluru, Karnataka 560068
BTM Layout: DataMites BTM branch, Starttopia, Ground Floor, Vinir Tower No 6, 100ft Main Road, 1st Stage, BTM Layout, Bengaluru, Karnataka 560068.
DataMites has 2 training centers in Pune: Kharadi and Baner.
Kharadi: office number 16, Second Floor, B Wing, City Vista, Downtown Rd, Ashoka Nagar, Kharadi, Pune, Maharashtra 411014
Baner: TRIOS Coworking Serviced Office Space 4th floor, Windsor Commerce, Baner Rd, near Hotel Wadeshwar, Baner, Pune, Maharashtra 411069
Datamites Institute in Hyderabad is located at Madhapur:
313, 4th Floor, Ayyappa Society Main Rd, Ayyappa Society, Megha Hills, Mega Hills, Madhapur, Hyderabad, Telangana 500081.
Datamites Institute in Coimbatore is located at Peelamedu, Coimbatore:
First floor, 1326/1, Avinashi Rd, Peelamedu, Coimbatore, Tamil Nadu 641004
DataMites has three training centers in Chennai: Guindy, Perungudi, and Anna Nagar:
Anna Nagar: A.J. COMPLEX, 1/1, Anna Arch Rd, AG Block, River View Colony, Anna Nagar, Chennai, Tamil Nadu 600040
Guindy:Door No. SP, Spero Primus, Primus Building, Awfis, 7A, Guindy Industrial Estate, SIDCO Industrial Estate, Guindy, Chennai, Tamil Nadu 600032.
Perungudi: 3rd Floor, Makers Tribe, 391A, above Saravana Bhavan, Nehru Nagar, Perungudi, Chennai, Tamil Nadu 600096.
Datamites Institute in Mumbai is located at Andheri East:
10th Floor, Crescent Plaza, Teli Gali, Bima Nagar, Andheri East, Mumbai, Maharashtra 400053
Datamites Institute in Ahmedabad is located at Navrangpura, Gujarat:
7th Floor, Manor Maxx, SV Desai Marg, Vasant Vihar, Navrangpura, Ahmedabad, Gujarat 380009
After completing the Certified Data Analyst course at DataMites, students receive IABAC and NASSCOM FutureSkills-accredited certifications along with other relevant credentials. These globally recognized certifications validate skills and boost career opportunities in data analytics.
DataMites provides extensive study materials, including e-learning resources, case studies, datasets, recorded sessions, and project guides. These resources complement live training, ensuring learners have access to both theoretical and practical knowledge
Yes, DataMites includes live projects in its Certified Data Analyst course in India. Students work on real-world case studies and datasets, gaining practical exposure that helps bridge the gap between classroom learning and industry applications.
Yes, if you miss a class, DataMites provides recorded sessions and backup classes. This ensures students never miss important topics and can continue their learning journey seamlessly without disruptions, keeping them aligned with the course schedule.
The DataMites Flexi Pass allows students to attend sessions for up to 3 months for the same course. It gives flexibility to rejoin classes, clarify concepts, and repeat sessions as needed, ensuring complete understanding of data analytics topics
Yes, DataMites offers demo classes before enrollment. This allows students to understand the teaching style, course structure, and faculty expertise, helping them make informed decisions before committing to the Certified Data Analyst course
DataMites stands out as a top choice with its IABAC and NASSCOM FutureSkills-accredited curriculum, expert mentors, internships, live projects, placement support, and offline centers across India. With flexible learning options, it caters equally well to both freshers and working professionals
DataMites offers multiple payment methods including credit/debit cards, net banking, UPI, EMI options, and wallets. These flexible choices make it easier for students to enroll in courses without financial constraints, ensuring accessibility for all learners
Yes, DataMites allows students to switch between offline and online modes for the Data Analyst course. This flexibility helps learners manage schedules, location preferences, and learning needs without interrupting their training journey
To enroll, visit the DataMites website, fill out the application form, or contact their support team. Choose your preferred learning mode (offline/online), complete payment, and get started with your Certified Data Analyst journey with expert guidance
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.
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