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  • IABAC® Certification
  • 6-Month | 200+ Learning Hours
  • 20 HOURS LEARNING A WEEK
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

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Self Learning + Live Mentoring

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  • Self Learning + Live Mentoring
  • IABAC® Certification
  • 1 Year Access To Elearning
  • 10 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Learner assistance and support

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WHY DATAMITES INSTITUTE FOR DATA ANALYTICS COURSES

Why DataMites Infographic

SYLLABUS OF DATA ANALYTICS COURSES

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 

  • Introduction to Statistics
  • Descriptive And Inferential Statistics
  • Basic Terms Of Statistics
  • Types Of Data

MODULE 2 : HARNESSING DATA 

  • Random Sampling
  • Sampling With Replacement And Without Replacement
  • Cochran's Minimum Sample Size
  • Types of Sampling
  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Random Sampling
  • Systematic Random Sampling
  • Multi stage Sampling
  • Sampling Error
  • Methods Of Collecting Data

MODULE 3 : EXPLORATORY DATA ANALYSIS 

  • Exploratory Data Analysis Introduction
  • Measures Of Central Tendencies: Mean, Median And Mode
  • Measures Of Central Tendencies: Range, Variance And Standard Deviation
  • Data Distribution Plot: Histogram
  • Normal Distribution & Properties
  • Z Value / Standard Value
  • Empherical Rule  and Outliers
  • Central Limit Theorem
  • Normality Testing
  • Skewness & Kurtosis
  • Measures Of Distance: Euclidean, Manhattan And MinkowskiDistance
  • Covariance & Correlation

MODULE 4 : HYPOTHESIS TESTING 

  • Hypothesis Testing Introduction
  • P- Value, Critical Region
  • Types of Hypothesis Testing
  • Hypothesis Testing Errors : Type I And Type Ii
  • Two Sample Independent T-test
  • Two Sample Relation T-test
  • One Way Anova Test
  • Application of 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

OFFERED DATA ANALYTICS COURSES

DATA ANALYTICS CAREER SUCCESS STORIES

DATA ANALYTICS COURSE REVIEWS

ABOUT DATA ANALYTICS COURSE

The Data Analytics course offered by DataMites is structured to provide learners with the fundamental skills required to analyze data, interpret results, and extract valuable insights. Datamites provides Certified Data Analyst Course spans approximately 6 months, providing over 200 hours of in-depth training. It covers key topics such as Excel, MySQL, Tableau, and no-code analytics tools, ensuring that students gain proficiency in industry-relevant technologies. DataMites offers a comprehensive curriculum that blends theoretical knowledge with practical applications, ensuring learners are industry-ready.

Certified Data Analyst Course is a 6-month certification program crafted to meet global industry standards. This comprehensive training module combines classroom & online instruction, live projects, and internships, offering valuable real-world exposure to students. 

Datamites Institute is accredited by prestigious organizations like IABAC and NASSCOM FutureSkills, the Data Analytics course stands out for its hands-on learning approach. Gaining proficiency in key tools such as Excel, SQL, Power BI, Python, and statistical analysis, preparing them for real-world data challenges.

According to a report published by SNS Insider via GlobeNewswire, the market was estimated at USD 52.68 billion in 2023 and is anticipated to surge to USD 483.41 billion by 2032 at a (CAGR) of 28.0% over the forecast period of 2024–2032.

Data Analytics is playing a pivotal role in the global digital transformation, driving informed decision-making across industries. As a core component of data science, it empowers organizations to interpret vast data sets, identify trends, and optimize strategies. With the rising demand for data-driven insights, skilled analytics professionals and comprehensive data analytics courses are increasingly essential for success in today’s data-centric world.

DataMites, a globally recognized leader in data science and analytics, offers a comprehensive Data Analytics course designed to equip learners with both theoretical knowledge and practical skills. With over 10 years of excellence and a hands-on learning approach, DataMites ensures career-ready expertise for diverse learners, making it an ideal choice for anyone aiming to advance in the data-driven world.

Data analytics is revolutionizing industries by enabling organizations to make informed, data-driven decisions, enhancing efficiency, and fostering innovation. In healthcare, analytics facilitates predictive diagnostics and personalized treatment plans, improving patient outcomes and reducing costs. Across various sectors, data analytics serves as a critical tool for enhancing operational performance and driving strategic growth.

The global demand for data analytics is experiencing unprecedented growth, driven by the exponential increase in data generation and the imperative for organizations to extract actionable insights. The global data analytics market is experiencing rapid growth, driven by the widespread adoption of artificial intelligence (AI), machine learning (ML), and big data technologies.

Industry-Specific Applications:

As industries continue to recognize the transformative power of data analytics, the demand for skilled professionals is set to rise, making it a pivotal area for career development and innovation.

  1. Healthcare: According to a McKinsey report, the U.S. healthcare system could potentially save between $300 billion and $450 billion annually by leveraging big data analytics to enhance operational efficiency, improve patient outcomes, and reduce waste.
  2. Finance: According to the Research gate, Big data analytics enhances financial forecasting, fraud detection, and resource allocation, while addressing challenges like data integration and privacy concerns. And firms with more data analysts often show better investment performance, highlighting the value of data expertise in financial decision-making .
  3. Manufacturing: Predictive analytics can reduce machine downtime by up to 45%, leading to significant cost savings and increased productivity. The Research Gate report emphasizes, Digital twin technology enhances smart manufacturing through real-time monitoring, predictive maintenance, and process optimization, improving efficiency and product quality.

The Precedence Research states that, In the Asia-Pacific region, the data analytics market is expected to grow at a CAGR of 23.5% from 2024 to 2034, reflecting the global trend of increasing reliance on data analytics for strategic planning and competitive advantage.

Key Job Roles in Data Analytics

Data analytics offers a diverse array of job roles, each with distinct responsibilities and skill requirements.

1. Data Analyst
Data Analysts interpret complex datasets to extract actionable insights, aiding businesses in decision-making. Proficiency in tools like SQL, Excel, and Tableau is essential.

2. Business Intelligence (BI) Analyst
BI Analysts develop dashboards and reports to monitor key performance indicators, enabling organizations to make informed strategic decisions. Proficiency in BI tools like Power BI and Tableau is crucial.

3. Data Engineer
Data Engineers design and maintain scalable data pipelines and infrastructure, ensuring efficient data flow for analysis. Gaining proficiency with big data technologies like Hadoop and Spark is important.

4. Machine Learning Engineer
Machine Learning Engineers create algorithms that enable systems to learn from data, automating predictive models. Proficiency in Python and frameworks like TensorFlow is required.

5. Analytics Manager
Analytics Managers lead data teams, translating analytical findings into business strategies. Strong leadership skills and experience with data analysis tools are necessary.

These roles are in high demand in Bangalore's thriving tech industry, offering competitive salaries and opportunities for career advancement.

Average Data Analyst Salaries Across Key Global Markets

Data analytics professionals are in high demand worldwide, with competitive salaries reflecting their expertise. As of 2025, the average annual salaries for Data Analysts  taken from Glassdoor are as follows:

  1. India: The average salary for a Data Analyst in India is ₹5 LPA to ₹10.5 LPA.
  2. United States: The salary of Data Analysts in the United States on an average is $55T to $86T annually.
  3. United Kingdom: The average salary of a Data Analyst in the UK is £28T - £43T annually.
  4. United Arab Emirates: The Data Analysts salary in Dubai on an average is AED 7T - AED 17T monthly.

These figures highlight the growing recognition of data analytics as a pivotal field across various industries, offering lucrative career opportunities globally.

Why Choose DataMites for Data Analytics Training?

DataMites offers industry-leading training designed to equip you with the practical skills and certifications needed to thrive in today’s data-driven world.

1. Expert-Led Training: DataMites offers data analytics training led by experienced industry experts, ensuring learners receive top-tier guidance. The course benefits from the leadership of seasoned professionals who bring deep knowledge of analytics tools and industry practices.

2. Internship Opportunity: Learners have the chance to gain real-world exposure through internship opportunities with leading companies. This practical experience is invaluable in bridging the gap between academic knowledge and industry application.

3. Comprehensive Curriculum: The Data Analytics program is carefully designed to cover essential topics, from foundational data handling to advanced analytical techniques. This curriculum suits beginners and professionals aiming to enhance their skills in data-driven decision-making.

4. Flexible Learning Modes:

  1. Classroom Training: Available in over 20 cities across India, including Bangalore, Chennai, Pune, Mumbai, and more, ideal for those who prefer face-to-face learning.
  2. Online Live Virtual Training: Real-time interactive sessions with instructors, accessible worldwide for flexible remote learning.
  3. E-Learning: Self-paced courses for learners who want to study at their own convenience.

5. Global Certification: DataMites is accredited by IABAC and NASSCOM FutureSkills, offering globally recognized certifications that boost your professional credibility in data analytics.

6. Placement Assistance: Our dedicated placement team supports learners with resume building, job references, and interview preparation. The Data Analytics course includes placement assistance (PAT) to connect learners with top companies across India, enhancing their career prospects.

7. Capstone Projects: Practical projects designed to apply analytical techniques to real-world scenarios, enhancing hands-on problem-solving abilities.

8. Practical Experience: Emphasis on hands-on learning through tools like Excel, Tableau, and SQL, enabling learners to gain industry-relevant skills.

9. Live Projects: Learners engage in multiple capstone and a live client projects that simulate real-world data challenges. This hands-on approach enables them to apply analytical techniques to actual business problems and gain practical insights.

10. Lifetime Access: Continue learning with lifetime access to course materials, allowing you to revisit key concepts anytime.

DataMites data analytics training provides a comprehensive, flexible, and practical learning experience that prepares you to excel in the fast-growing field of data analytics.

Internships and Placement Support 

DataMites offers Data Analytics courses with internship opportunities and placement support, ensuring learners gain practical experience through real-world projects. The dedicated Placement Assistance Team prepares students for the job market with resume building and interview training. Through exclusive collaborations with top IT companies, students engage in tailored internships, applying data analytics skills to real business challenges under expert mentorship.

DataMites Offline Centers

DataMites offers comprehensive data analytics courses in India through offline training centers located in major cities such as Bangalore, Pune, Hyderabad, Chennai, Coimbatore, Ahmedabad, Kolkata, Delhi, Indore, Bhubaneswar, Jaipur, Kochi, Nagpur, Chandigarh and Mumbai and several other key cities. These centers provide in-person, expert-led instruction, enabling students and professionals to gain practical, hands-on experience in data analytics. 

With state-of-the-art facilities and a collaborative learning environment, DataMites offline centers are ideal for those who prefer classroom-based instruction. The data analytics courses at these centers combine theoretical knowledge with hands-on practice, enabling learners to gain real-world insights and practical skills essential for thriving in the field of data analytics.

Top Data Analytics Courses at DataMites

Certified Data Analyst Course

The Certified Data Analyst Course is an extensive 6-month program designed for individuals aiming to build a solid foundation in data analytics. This course offers 200+ learning hours for in-depth learning, including 20 hours of dedicated study per week. The curriculum is carefully structured to start with the fundamentals of data analytics and advance through critical topics such as data visualization, statistical analysis, and business intelligence tools.

Participants will work on 10 hands-on capstone projects and one client or live project to gain valuable practical experience. The program focuses on preparing learners for the job market by providing globally recognized certifications, an internship experience certificate, and comprehensive job readiness training.

The course covers a broad range of topics, beginning with essential data analytics concepts like data cleaning, exploratory data analysis, and Excel proficiency. It also includes advanced modules on SQL, Tableau, Power BI, and Python for data analysis. Learners will gain expertise in statistical methods, data storytelling, and data-driven decision-making.

Additionally, the program explores real-world applications across industries such as finance, marketing, and healthcare. By the end of the course, participants will be skilled in analyzing complex datasets, creating impactful visualizations, and delivering actionable insights, making them highly effective data analysts ready to succeed in any professional environment.

Three-Phase Learning Methodology for Data Analytics at DataMites

At DataMites, our structured Three-Phase Learning Methodology ensures learners gain the knowledge, skills, and experience required to excel in data analytics careers.

The DataMites Data Analytics course follows a structured three-phase learning path to ensure thorough skill development. Phase 1 – Preparation focuses on self-paced learning through videos, eBooks, and modules covering core analytics concepts and tools. Phase 2 – Intensive Training features expert-led live sessions and hands-on capstone projects, culminating in a globally recognized IABAC certification. Phase 3 – Project and Internship provides real-world exposure through live projects and internship opportunities, bridging theory with practice. Learners also benefit from resume building, interview coaching, and placement support, making them job-ready and confident to pursue rewarding careers in the dynamic field of data analytics.

Begin Your Data Analytics Journey with DataMites

Data analytics is more than just a career it’s a powerful pathway that transforms businesses and drives smart decision-making across industries. At DataMites Institute, we are dedicated to providing top-quality resources, thorough training, and continuous support to help you thrive in this dynamic field. As a premier Institute, we prepare aspiring professionals with the essential skills and knowledge to succeed in data analytics.

Our Data Analytics training programs are crafted to equip you with the latest tools, techniques, and industry best practices, ensuring you stay competitive and future-ready. Whether you’re a beginner or looking to sharpen your analytics expertise, DataMites Institute offers a variety of specialized courses in Data Science, Data Analytics, Artificial Intelligence and Machine Learning, Data Engineering, and Python Programming tailored to every skill level.

DataMites is a premier institute offering comprehensive Data Analytics courses designed to equip learners with in-demand skills through a blend of expert-led training, hands-on projects, and industry certification. Whether you're a beginner or a working professional, DataMites ensures a strong foundation in analytics tools, techniques, and real-world applications. 

The course includes self-paced learning materials, interactive live sessions, and practical exposure through capstone projects and live industry-based assignments. Learners also benefit from internship opportunities, placement assistance, resume support, and interview coaching, making them job-ready. With global certifications like IABAC, DataMites empowers you to advance confidently in your data analytics career.

Take your first step toward becoming a skilled data analyst today. Enroll in our comprehensive training programs and unlock a world of career opportunities, innovation, and growth in the exciting realm of data analytics!

ABOUT DATAMITES DATA ANALYTICS COURSES

Career options include Data Analyst, Business Analyst, Data Scientist, BI Analyst, Market Research Analyst, and Data Engineer. These roles span industries like IT, finance, healthcare, retail, and e-commerce, with strong demand for data-driven decision making.

A Data Analytics course equips you with skills to analyze, interpret, and visualize data to drive business decisions. It opens high-demand career paths, enhances problem-solving skills, and provides hands-on experience with tools and real-world projects for job readiness.

The duration typically ranges from 3 to 6 months depending on the institute and course intensity. Some offer accelerated bootcamps of 1-2 months, while detailed programs with internships may last up to 6 months for in-depth learning.

The cost of Data Analytics courses varies based on the course level and institution. Basic courses typically range from ₹10,000 to ₹2,00,000, while advanced programs can cost between $500 to $2,500. These figures are approximate and can differ depending on the provider and location. 

Look for institutes with comprehensive curriculum, expert trainers, real-world projects, certification, positive reviews, and placement support. Industry connections and internship opportunities also indicate quality and practical training.

As per a report by SNS Insider via GlobeNewswire, the global data analytics market was valued at USD 52.68 billion in 2023 and is expected to grow at a CAGR of 28.0%, reaching USD 483.41 billion by 2032 during the forecast period of 2024–2032. Sectors like finance, healthcare, retail, and IT are actively hiring data analysts, making analytics skills highly sought after in today’s job market.

Globally, Data Analysts varies based on experience, location, and industry. Entry-level roles start lower, while experienced analysts in tech hubs earn significantly more. According to Glassdoor,

  • United States: Data Analysts earn between $55K and $86K annually on average.
  • United Kingdom: The average annual salary for a Data Analyst is £28K to £43K.
  • United Arab Emirates (Dubai): Data Analysts earn approximately AED 7K to AED 17K per month.
  • India: The average salary for a Data Analyst ranges from ₹5 LPA to ₹10.5 LPA.
  • Spain: Data Analysts in the Spain earn an average salary ranging from €26T - €40T per year.

No, a strong math or CS background is helpful but not mandatory. Many courses start from basics, making it accessible for beginners. Analytical thinking and eagerness to learn tools like Excel, SQL, and Python matter most.

Popular data analyst tools include Excel, SQL, Python, R, Tableau, Power BI, SAS, and Google Analytics. These help in data extraction, cleaning, analysis, visualization, and reporting to support decision-making.

The four types of data analytics are:

  • Descriptive Analytics – Summarizes past data to understand what happened.
  • Diagnostic Analytics – Examines data to find out why something happened.
  • Predictive Analytics – Uses historical data to forecast future outcomes.
  • Prescriptive Analytics – Recommends actions based on predictive insights.

Typically, basic computer knowledge and analytical mindset suffice. Some familiarity with spreadsheets or programming helps but is not essential. Beginners-friendly courses often provide foundational training.

Data Analytics is the process of collecting, cleaning, analyzing, and interpreting data to uncover patterns, trends, and insights that aid in decision-making and strategic planning.

Data Analytics focuses on analyzing historical data to provide actionable insights. Data Science involves a broader scope including predictive modeling, machine learning, and advanced algorithms to create data-driven products.

According to Precedence Research, the Asia-Pacific data analytics market is projected to grow at a 23.5% CAGR from 2024 to 2034. Data Analytics skills align with increasing demand for data-driven business strategies. With digital transformation accelerating, companies seek professionals who can interpret data for competitive advantage.

Data Analysts apply their core skills across industries with tailored focuses: in finance, they handle risk assessment, fraud detection, and financial forecasting; in healthcare, they analyze patient data to improve care and predict health trends; in retail, they study customer behavior and sales to boost marketing and inventory; and in technology, they examine product usage and system performance to enhance products and operations.

Handling large, unstructured datasets and ensuring data accuracy while deriving meaningful insights is challenging. Balancing technical skills with business understanding is also crucial.

Its ability to analyze any data type—from sales, finance, marketing, to healthcare—makes it adaptable. The cross-industry application ensures relevance regardless of domain or sector.

Anyone with curiosity, analytical thinking, and basic computer skills can learn Data Analytics. The course is beginner-friendly and suitable for students, professionals, and career changers.

Both India and global markets show strong growth in data roles across IT, finance, healthcare, e-commerce, and consulting. Opportunities span startups to multinational corporations with attractive salaries.

Key skills include Excel, SQL, Python/R, data visualization (Tableau/Power BI), statistics, data cleaning, and basic knowledge of machine learning concepts. Strong communication skills are also vital.

Top IT companies hiring Data Analysts globally include Google, Amazon, Microsoft, IBM, Facebook, Deloitte, Accenture, and JPMorgan Chase. These firms seek skilled analysts to drive data-driven decisions across tech, finance, consulting, and retail sectors.

Current data analytics trends include growing demand for AI and machine learning skills, emphasis on soft skills like communication, rise of remote work, focus on data privacy, shift to skill-based hiring, and increasing use of cloud analytics for scalable, efficient data solutions.

Popular data analytics tools include Excel, Power BI, Tableau, SQL, Python libraries (Pandas, NumPy), R, SAS, Hadoop, and Spark. These tools help with data cleaning, visualization, statistical analysis, and big data processing, enhancing analytics capabilities.

Python is widely used in data analytics for data manipulation, visualization, and statistical modeling. Libraries like Pandas, NumPy, and Matplotlib enable efficient data processing, while machine learning libraries like Scikit-learn help build predictive models.

Data Analytics courses include projects like sales trend analysis, customer segmentation, financial forecasting, social media sentiment analysis, and dashboard creation. These practical projects build hands-on skills in real-world data handling and decision-making.

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FAQ’S OF DATA ANALYTICS TRAINING COURSE

DataMites offers expert-led training, hands-on live projects, comprehensive curriculum, internship opportunities, and strong placement support. Its industry-focused approach ensures practical skills for a successful career in Data Analytics, making it a preferred institute.

Yes, DataMites provides internship opportunities with its Data Analytics course. These internships offer real-world experience, helping students apply their skills practically and gain confidence for job readiness in the competitive data analytics market.

Yes, DataMites offers flexible EMI options for the Data Analytics course. This allows students to pay fees in convenient installments, making it easier to invest in quality education without financial stress.

Yes, DataMites offers free demo classes for the Data Analytics course. This helps you understand the course structure, teaching style, and content before making your enrollment decision, ensuring confidence in your learning choice.

The Data Analytics course fee at DataMites ranges from ₹20,000 to ₹70,000, depending on the program type—online or offline—and the chosen payment plan. For accurate and up-to-date pricing, it is recommended to visit the official DataMites website or contact their support team directly.

Yes, DataMites provides placement assistance with its Data Analytics course. They connect students with reputed companies and support interview preparation, helping graduates secure jobs in data analytics and related fields.

DataMites offers a transparent refund policy. If you cancel within the initial days of enrollment, you are eligible for a partial refund. Detailed terms and conditions are available on their official website for full clarity.

DataMites provides extensive study materials including e-books, assignments, project work, and access to an online learning portal. These resources ensure comprehensive understanding and support throughout your Data Analytics learning journey.

DataMites instructors are industry experts with vast experience in Data Analytics. They bring practical knowledge and real-world insights to training, ensuring that students learn current industry standards and skills effectively.

Yes, the Data Analytics course at DataMites includes live projects. These projects provide hands-on experience with real-world datasets and scenarios, enhancing practical skills essential for career success.

The Data Analytics course duration at DataMites is typically 6 months. This timeframe covers foundational to advanced topics, ensuring a thorough understanding and job readiness in data analytics.

Yes, DataMites offers flexibility for missed classes. You can attend the missed sessions in another batch or access recorded classes to stay on track with your Data Analytics course without losing valuable learning time.

After completion, DataMites awards a globally recognized Data Analytics certification. This validates your skills and knowledge, boosting your resume and enhancing job opportunities in the data analytics field.

You will learn data analysis, visualization, statistics, SQL, Python/R, machine learning basics, and business intelligence tools. These skills prepare you to handle real-world data and solve business problems effectively.

DataMites Flexi Pass offers flexible access to online Data Analytics classes, allowing you to attend sessions anytime across multiple batches. It suits learners needing convenience without compromising on quality education and interaction.

DataMites has multiple centers across India, including major cities like Bangalore, Pune, Hyderabad, Chennai, Coimbatore, Ahmedabad, Kolkata, Delhi, Indore, Bhubaneswar, Jaipur, Kochi, Nagpur, Chandigarh and Mumbai. This extensive network ensures easy access to quality Data Analytics training nationwide.

DataMites offers flexible payment options including online payments via credit/debit cards, net banking, UPI, and EMI plans. These choices make it convenient for students to pay for Data Analytics courses based on their financial comfort.

Yes, DataMites allows flexible switching between offline and online Data Analytics. Students can shift modes as per convenience without losing access to course content or support, ensuring seamless learning continuity.

DataMites offers a comprehensive curriculum, expert faculty, hands-on projects, internships, and placement support. Their industry-focused approach equips students with practical skills needed to excel in Data Analytics careers.

To enroll, visit the official DataMites website, select the Data Analytics course, fill out the registration form, choose your batch and payment plan. The team will assist you throughout the process for smooth enrollment and course commencement.

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: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

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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