Job-Oriented Data Analytics Course and Training
The Data Analytics course offered by Rexton IT Solutions will help take your career to the next level. The course includes Live Online sessions and Classroom Training. The training sessions consist of an industry-relevant curriculum, including projects, a practicum, and hands-on training with tools, to help you understand the fundamental application of data analytics in the real world. Our course includes essential tools such as Power BI, Excel, Python, Tableau, and SQL, which are in high demand in today’s job market.
Moreover, the data analytics course consists of the benefits of both online and offline classes. Likewise, the course also includes 100% placement support, including resume production, placement, and mock interviews, to help you take the first step into the actual world of employment. Additionally, the expert trainers at Rexton IT Solutions will teach you to make a successful career in data analysis.
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Why is This Data Analytics Course Different?
At Rexton IT Solutions, a Data analytics course stands out through its focus on real-world projects/portfolios, practical, job-ready skills, personalized learning paths (advanced vs. beginner), industry-expert instructors, and specific tool emphasis (Excel, SQL, Python, Tableau), often blending technical training with imperative soft skills like critical thinking and communication for business problem-solving. Furthermore, key differentiators include hands-on labs for a ready-to-join application, tailored curricula, and portfolio building that cater to a wide range of backgrounds. Nevertheless, here are some vital reasons why you need this course to build your IT career:
- Career Placement Support – Build and Grow Your Future with Us
- Flexible Learning Modes – Online & Offline Classes Designed for You
- Personalized 1-on-1 Training – Get Personalized Guidance and Clarify Every Doubt
- Mock Interviews – Be Fully Prepared for Technical Interviews
- Lifetime Learning – Unlimited Revision Classes
- Practical Exposure – Industry-Ready Labs for Real-World Practice
Our flexible approach helps you balance personal commitments while gaining in-demand technical skills, making your learning journey smooth, efficient, and career-focused.
- Offline Classroom Training : For students who prefer classroom learning, Rexton IT Solutions has provided offline classroom training. In a classroom, you learn with the help of tutors, get hands-on training, and the classroom environment ensures you are motivated.
- Live 1-1 Doubt Sessions : If you want some individual attention, 1-on-1 sessions will work best for you. In these sessions, you will get exclusive access to a trainer, with flexible timings and everything adjusted to your level.
- Covering all the basic Data Analysis concepts and including all the topics like Data Cleaning, Data Visualization, Statistics Analysis, SQL, Python, Power BI, and Tableau.
- Practical training sessions led by experts in the industry, so the concepts can be explained in a simplified manner, making it easy for everyone to understand.
- Enjoy personalized 1-on-1 doubt clearance sessions to help you learn at your own pace and immensely boost your understanding of complex analytics concepts.
- Practice the application of concepts to real-world datasets, business cases, and live assignments that imitate real-world business situations to improve your skills.
- Data Analytics training from Rexton IT Solutions will equip you with the skills, confidence, and guidance to pursue lucrative job openings.
Why Choose Rexton IT Solutions for Data Analytics Training
When you enroll with Rexton IT Solutions, you are offered more than a Data Analytics learning course because here you will have a comprehensive learning experience. Industries are also taken into consideration when structuring the learning process, which will include both conceptual learning and hands-on exposure. With the online learning option, you will be able to learn from experienced faculty members from the comfort of your home. If you are a beginner or a professional, learning will become flexible and job-oriented after choosing the right learning option from Rexton IT Solutions. Here are some imperative reasons why you should opt for Rexton IT Solutions for the Data Analytics Course:
Trainers can clearly and effectively explain the concept by drawing on their industry experience in real time.
Practical learning experience with real-world datasets and projects.
Session recording facilities are also provided for classes or sessions that are missed or require revision.
These are live online classes where you can ask questions directly to the trainers.
Convenient class timings for both working professionals and students.
Resume development assistance, interview preparation assistance, and career counseling.
Beginner-Friendly Approach: No prior technical knowledge or training from basic to advanced level.
Training Features
1-on-1 Training
Clear All Your Doubts
Flexible Learning
Online and Offline Classes for Self-paced Learning
Mock Interviews
Complete Preparation for Technical Interview Rounds
Placement Support
Start and Grow Your Career with Us
Job-Oriented Learning
Who Can Enroll in our Data Analytics Training Course
Our Data Analytics Training Course is for everyone eager to learn how to turn data into meaningful insights. Whether you are a graduate student or a working professional, this program is designed to help you build practical, job-ready analytics skills. Our Data Analytics Training course is best for:
- Students & Fresh Graduates
- Software Developers
- Support Engineers
- Finance, Banking, Accounting professionals
- Data Analyst
- Professionals Seeking Advancement
- Business Owners & Entrepreneurs
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What Do You Need to Know Before Enrolling in the Data Analytics Course
One of the vital advantages of the Data Analytics course is its open entry with no prior qualification requirements. Whether you are an academic student or a real-time expert, you can enroll in our Data Analytics course online. Nevertheless, having a basic understanding of networking can accelerate your overall progress. Furthermore, knowing the related technical concepts can make the learning journey smoother and less complicated. Additionally, other fundamental topics that will help you during the Data Analytics course include:
- Basic Mathematics and Statistics
- Understanding of Data Types and Structures
- Microsoft Excel Fundamentals
- Logical and Analytical Thinking
- Basic Computer and Internet Skills
- Introduction to Databases and SQL Concepts
- Data Visualization Basics
- Problem-Solving Skills
- Attention to Detail and Data Accuracy
- Basic Business and Domain Knowledge
| Category | Details |
|---|---|
| Exam Name | Data Analytics Course Final Assessment |
| Exam Type | Online / Proctored / Classroom-based (varies by provider) |
| Assessment Format | Multiple Choice Questions (MCQs), Practical Assignments, Case Studies, Project Evaluation |
| Total Duration | 2–3 Hours |
| Number of Questions | 50–100 (including theory and practical tasks) |
| Passing Criteria | 60%–70% overall score |
| Mode of Examination | Online (LMS-based) or Offline |
| Skill Areas Tested | Statistics, Excel, SQL, Data Visualization, Python/R, Business Analytics |
| Practical Component | Hands-on data analysis, dashboards, and real-world datasets |
| Project Submission | Mandatory (individual or group project) |
| Tools Covered in Exam | Excel, SQL, Power BI/Tableau, Python (as applicable) |
| Certification Issued | Course Completion / Professional Certification |
| Eligibility to Appear | Completion of course modules and assignments |
| Number of Attempts | 1–3 attempts (as per institute policy) |
| Re-exam Policy | Retake available with additional fee or revision training |
| Result Declaration | Immediate (online exams) or within 7–10 working days |
| Certification Validity | Lifetime / As specified by the training provider |
| Difficulty Level | Beginner to Intermediate |
| Exam Language | English |
- Data Analytics Fundamentals – Introduction to Data Analytics, types of analytics (descriptive, diagnostic, predictive, prescriptive), data lifecycle, real-world use cases across industries.
- Statistics & Data Foundations – Data types and structures, descriptive and inferential statistics, probability concepts, distributions, correlation, and hypothesis testing basics.
- Excel for Data Analysis – Data cleaning and formatting, formulas and functions, Pivot Tables, charts, lookups, conditional formatting, and dashboard creation.
- SQL for Data Analytics – Database concepts, SELECT queries, filtering and sorting data, JOINs, GROUP BY and HAVING clauses, subqueries, views, and performance basics.
- Data Cleaning & Preparation – Handling missing values, duplicates, and outliers, data transformation, normalization, and validation techniques.
- Python for Data Analytics – Python fundamentals, NumPy and Pandas, data manipulation, exploratory data analysis (EDA), and basic scripting for analytics.
- Data Visualization & BI Tools – Principles of data visualization, Power BI / Tableau, interactive dashboards, charts, KPIs, and data storytelling.
- Business Analytics & Case Studies – Understanding business problems, defining KPIs, data-driven decision making, and industry-based case studies.
- Capstone Project – End-to-end real-world data analytics project covering data collection, analysis, visualization, and insight presentation.
- Configuration & Hands-on Practice
- Interview Preparation
- Exam Preparation
This real-time course outline gives you a quick overview of our comprehensive Data Analytics course. Furthermore, the entire program offers in-depth knowledge with hands-on assessments, real-world projects, and assignments. Additionally, to explore the whole academic curriculum, feel free to contact our course representative for more details.
Course Features
Here, we have mentioned the learning materials you will receive after enrolling in our Data Analytics Course:
Structured Course Notes & eBooks, Video Tutorials, Assignments, and Case Studies
Access to Analytics Tools (Excel, SQL, Tableau, Python, R)
Job-Oriented Resources (resume tips, interview prep)
Quizzes & Practice Exercises, Datasets for Practice
Webinars & Expert Sessions
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Benefits of Our Comprehensive CCNA Training and Course
Certified Professionals & Experts
Industry-oriented curriculum
AI-driven Learning
High-Paying Role after Data Analytics Training
| Role | Typical Salary Range (INR per year) |
|---|---|
| Data Scientist | ₹5 L – ₹30 LPA |
| Data Engineer | ₹8 L – ₹25 LPA |
| Business Intelligence (BI) Analyst | ₹4.5 L – ₹16 LPA |
| Business Analyst | ₹7 L – ₹15 LPA |
| Machine Learning / AI Analyst | ₹10 L – ₹20 LPA |
| Product / Data Insights Analyst | ₹10 L – ₹18 LPA |
| Quantitative Analyst (Quant) | ₹12 L – ₹32 LPA |
| Data Analytics Specialist | ₹3 L – ₹30 LPA |
| Senior Data Analyst | ₹12 L – ₹28 LPA |
| Analytics / BI Manager | ₹18 L – ₹40 LPA |
The above salaries depend heavily on location, experience, industry type, and company size. Furthermore, advanced roles such as Data Architect, Machine Learning Engineer, and Quantitative Analyst tend to command higher salaries, especially in tech hubs and global markets.
The career paths you can explore after completing our Data Analytics course go far beyond the ones listed here. Moreover, there are plenty of exciting opportunities waiting for you. Get in touch with us for personalized advice and guidance to help shape your next career move.
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Frequently Asked Questions
The data analyst’s role involves analyzing data from various sources, cleaning it as needed, interpreting it, identifying patterns and trends, and presenting these findings in a format valid for business decision-making. They help to interpret data into meaningful narrative formats for business decision-makers. They act as a connection between data and business.
The different categories of analytics, namely descriptive, predictive, prescriptive, and diagnostic analytics, give a business the capacity to examine the past, the future, and optimize future results. Furthermore, the process begins by identifying your business questions and the type of analytics you would like to perform.
Yes, the demand for data analysts is still high in 2025. Every industry in the world uses data to make smarter decisions, improve performance, and stay competitive. In addition, skilled data analysts remain overtly important, well-paid, and highly valued professionals as AI, digital transformation, and big data take center stage.
Among these key skills required for data analysts are:
- Structured Query Language (SQL)
- Machine Learning
- Statistical programming in R or Python
- Microsoft Excel
- Presentation skills
- Critical thinking
- Data Visualization
The four pillars of data analysis can be compared to the following four tools that enable business entities to understand data:
- Descriptive Analysis
- Case Study
- Predictive Analysis
- Prescriptive Analysis
