Data Analytics Course in India

Data Analytics Course in IndiaClassroom batchPlacement SupportInternship Support

Data Analytics CourseLearn Excel, SQL, Power BI, Tableau and Python

Name: Skillonit
Address: 3rd Floor, Shrishantul Tower, Chikhali Rd, Buldana, Maharashtra, 443002, IN
Telephone: +91 7083384100

No advanced programming background is required to begin. Learners receive a step-by-step foundation and gradually work toward more independent analysis. The exact duration, delivery mode, trainer, batch schedule and fees are displayed from the current approved course record so that every enrollment decision is based on accurate information.

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap. Practice data cleaning, reporting, dashboard design and business-focused analysis. Complete assignments, case studies, mini projects and a guided capstone portfolio. Develop the communication skills needed to explain insights to technical and non-technical audiences. Access career and placement assistance according to the services included in the active batch.

Duration24 weeks

LanguagesHindi | English | Marathi

Rating4.8/5

Learners2,640

In-campus classroom training

Learners who want face-to-face teaching, fixed batches, and local classroom guidance.

Included in this mode

Instructor-led classroom sessionsIn-person doubt solvingComputer lab practiceBatch-wise assignments and tests

Learning flow

1Classroom orientation

2Guided practical sessions

3Weekly mentor review

4Project and certificate assessment

Why Learn Data Analytics Now?

Organizations collect more operational, customer, financial and digital data than many teams can use effectively. The challenge is no longer only obtaining data; it is preparing it correctly, defining reliable metrics and turning it into understandable decisions. This creates a continuing need for people who can work between raw information and business action. For professionals, the same skills support better reporting, automation and decision-making. A repeatable Power Query process can reduce manual spreadsheet work; a well-designed SQL query can replace error-prone copying; a Power BI semantic model can create consistent KPIs; and a clear dashboard can help teams act faster.

Learn Excel and SQL analysisBuild Power BI reportsInterpret business metricsPractice case studies

Best Data Analytics Course in India: What a Strong Program Should Deliver

Projects should require learners to make decisions. Copying a finished dashboard is not the same as analyzing data. A strong project asks the learner to inspect data quality, define useful metrics, justify chart choices, calculate KPIs, document assumptions and present recommendations. Feedback should evaluate both technical accuracy and clarity of communication. Transparency is equally important. Before enrolling, learners should be able to review the current syllabus, actual delivery mode, expected practice time, batch schedule, fees, trainer information, certificate conditions, recording policy and career-support services. Any claim about guaranteed employment, salary, interview rates, trainer experience, partnerships or external recognition should be supported by current evidence.

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap.

Practice data cleaning, reporting, dashboard design and business-focused analysis.

Complete assignments, case studies, mini projects and a guided capstone portfolio.

Develop the communication skills needed to explain insights to technical and non-technical audiences.

Complete Data Analytics Course Syllabus

Active module

Foundation

7 lessons

1Business questions, dimensions and measures

2KPIs, metrics and targets

3Analytical workflow and documentation

4Ethics, privacy and responsible interpretation

5Guided practice: Translate a business scenario into a question tree, metric definition sheet and analysis plan.

6Module 2: Microsoft Excel Fundamentals for Analysts

7Workbook and worksheet structure

Upcoming Batch Schedule

Selected batch

Classroom Batch

Start DateUpcoming

TimingsRegular live sessions

Duration16 weeks

ModeClassroom

Learn with Data Analytics Mentors

Supports learners with AI, machine learning, data science concepts, applied projects, and analytical thinking.

Prathamesh Pathak focuses on practical Data Analytics training with a learner-first approach. Sessions combine clear concept explanation, demonstrations, lab-based practice, and interview-oriented guidance so students understand how the skill is applied in real work.

Concept clarityProject practicePortfolio mentoring

Concept-first explanations

Hands-on practice and assignments

Project and portfolio guidance

Doubt-solving support

Career-oriented mentoring

Responsible tool usage and documentation

Data Analytics Certification Program

The certificate section should state the exact eligibility rules, issuing organization, issue date, credential or verification identifier where available, and the process for correcting a learner’s name. A sample image may be displayed only when it matches the certificate that will actually be issued. Learners should support the credential with practical evidence: Excel workbooks, SQL case studies, dashboards, notebooks, project documentation and a concise presentation. Employers commonly evaluate what a candidate can explain and demonstrate, not only the certificate title.

Course-completion certificate

Assignment and project-based validation

Useful for resume and portfolio building

Certificate details subject to current course policy

Certificate ID

SKL-DAT-2026

Certificate of Completion

Data Analytics Specialist

This certifies that the student has completed Skillonit’s Data Analytics training with practical tasks, quizzes, and project assessment.

Presented to

Student Name

For successful completion of Data Analytics Course

Completion Date

18 Jun 2026

★

Authorized Signature

Verification-ready certificate preview for LMS completion.

Program at a Glance

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap.

Practice data cleaning, reporting, dashboard design and business-focused analysis.

Complete assignments, case studies, mini projects and a guided capstone portfolio.

Develop the communication skills needed to explain insights to technical and non-technical audiences.

Access career and placement assistance according to the services included in the active batch.

Business questions, dimensions and measures

KPIs, metrics and targets

Analytical workflow and documentation

Ethics, privacy and responsible interpretation

Workbook and worksheet structure

Data types and formatting

Excel tables and structured references

Tools students practice

Data AnalyticsAnalyticsAnalytics basicsExcel and SQLPower BI dashboardsBusiness case reporting

Start Building Practical Data Analytics Skills

This course blends clear concepts, practical training, guided projects, quizzes, and career-focused assessment to help learners build confidence and move toward real opportunities.

Learn core foundations

Practice with guided tasks

Complete project assessment

Prepare for career roles

Module 22: Capstone Project and Analytics Presentation

The capstone brings the full workflow together. Learners select or receive a realistic business case, clarify the questions, inspect and prepare the data, use appropriate tools, build a report or dashboard and present recommendations. Assessment should reward accuracy, reasoning, documentation and communication rather than visual appearance alone. Learner outcome: Demonstrate a connected Data Analyst workflow in a portfolio-ready capstone.

Role-focused learning

Live project practice

Portfolio-ready skills

Freshers beginning a data career

Freshers who are uncertain where to begin receive a sequential roadmap. The course starts with computer and data foundations, develops tool confidence and repeatedly connects technical work to business questions. BCom, BBA, MBA and commerce learners Commerce and management learners often understand finance, marketing or operations but need stronger technical analysis skills. Excel, SQL, Power BI and business metrics can help them combine domain knowledge with data-driven reporting. BCA, BSc, MCA and engineering learners A technology degree is not mandatory. Non-IT learners should be prepared to practise consistently, learn database concepts and become comfortable with structured problem solving. The program introduces the required foundations gradually.

Placement Support Includes

BCom, BBA, MBA and commerce learners

Commerce and management learners often understand finance, marketing or operations but need stronger technical analysis skills. Excel, SQL, Power BI and business metrics can help them combine domain knowledge with data-driven reporting.

BCA, BSc, MCA and engineering learners

Non-IT learners

A technology degree is not mandatory. Non-IT learners should be prepared to practise consistently, learn database concepts and become comfortable with structured problem solving. The program introduces the required foundations gradually.

Working professionals

MIS executives and reporting professionals

Learners already working with spreadsheets can deepen their skills through Power Query, SQL, data modelling, DAX, dashboard design and validation methods.

Why Students Trust Us

Transparency is equally important. Before enrolling, learners should be able to review the current syllabus, actual delivery mode, expected practice time, batch schedule, fees, trainer information, certificate conditions, recording policy and career-support services. Any claim about guaranteed employment, salary, interview rates, trainer experience, partnerships or external recognition should be supported by current evidence.

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap.

Practice data cleaning, reporting, dashboard design and business-focused analysis.

Complete assignments, case studies, mini projects and a guided capstone portfolio.

Develop the communication skills needed to explain insights to technical and non-technical audiences.

Access career and placement assistance according to the services included in the active batch.

Business questions, dimensions and measures

KPIs, metrics and targets

Analytical workflow and documentation

Admission enquiry

Talk to a Skillonit counsellor

Share your details and our team will help you choose the right Data Analytics batch, learning mode, syllabus, fee plan, and career path.

Request Callback+91 7083384100

Download SyllabusData Analytics course outline

WhatsApp GuidanceFast response from counsellor

Who Should Join the Data Analytics Course?

Students and recent graduates College students and graduates can use the program to build practical evidence beyond academic marks. A portfolio containing Excel analysis, SQL queries, Power BI dashboards, a Python notebook and a capstone case study can help demonstrate learning in internships and entry-level interviews. Freshers beginning a data career Freshers who are uncertain where to begin receive a sequential roadmap. The course starts with computer and data foundations, develops tool confidence and repeatedly connects technical work to business questions. BCom, BBA, MBA and commerce learners Commerce and management learners often understand finance, marketing or operations but need stronger technical analysis skills. Excel, SQL, Power BI and business metrics can help them combine domain knowledge with data-driven reporting.

Career roles

Analytics Trainee

Build strong foundation skills in Data Analytics

Project Intern

Apply concepts through guided practical projects

Freelance Beginner

Use portfolio work to start client-ready practice

Career Starter

Prepare for internships, jobs, or higher learning

Best Data Analytics Course in India: What a Strong Program Should Deliver

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap.

Practice data cleaning, reporting, dashboard design and business-focused analysis.

Complete assignments, case studies, mini projects and a guided capstone portfolio.

Develop the communication skills needed to explain insights to technical and non-technical audiences.

Access career and placement assistance according to the services included in the active batch.

Business questions, dimensions and measures

KPIs, metrics and targets

Analytical workflow and documentation

Learn Excel, SQL, Power BI, Tableau and Python in one connected Data Analytics roadmap.

Practice data cleaning, reporting, dashboard design and business-focused analysis.

Internship Program

Data Analytics Internship Program in India

Skillonit’s Data Analytics Internship Program in India is a mentor-guided practical pathway available in 1-month, 3-month and 6-month formats. Participants learn how to convert raw business data into reliable reports, dashboards, KPIs and decisions using Excel, SQL, Power BI, Tableau and Python. The program combines structured training, assignments, project reviews, documentation, portfolio support and a completion certificate subject to published requirements.

The internship is designed for students, commerce and management graduates, professionals, business users, analysts and career switchers. It turns course knowledge into structured practice through mentor-led onboarding, guided tasks, project milestones, review meetings, documentation and a final presentation. Participants are expected to build, test, explain and improve their work instead of only watching demonstrations.

1 month3 months6 monthsIndia

Apply Now

Available durations

1 month, 3 months and 6 months

Delivery modes

Live online, classroom or hybrid—subject to the selected batch and location

Learning model

Training + mentor-guided tasks + project reviews + portfolio evidence

Projects

Mini project, guided projects and capstone according to duration

Support

Onboarding, doubt clearing, task planning, review feedback and presentation guidance

Certificate

Issued after required attendance, submissions, evaluation and final presentation

About Program

About the Internship Program

Skillonit’s Data Analytics internship is designed as a bridge between learning and practical delivery. Interns begin with a baseline assessment and a clear task plan, then progress through demonstrations, guided exercises, independent work and review. The focus is on understanding why a solution works, how to communicate decisions and how to improve quality after feedback.

The work is aligned with Excel, data cleaning and structured reporting, Power BI or Tableau dashboard development and data modelling, DAX and advanced SQL. Longer pathways include more complex requirements, collaboration, documentation, testing and presentation. Interns maintain a task log or project board so that progress can be reviewed objectively rather than judged only by the final output.

The internship does not guarantee employment, freelance income, client allocation or a stipend. It provides practical exposure, evidence of completed work and career-readiness support. Any employment or paid internship opportunity is published separately with its own eligibility, application deadline, compensation and selection process.

Duration Options

Choose your internship duration

Option 1

1-Month Data Analytics Foundation Internship

The one-month pathway is a focused four-week experience for learners who want an introduction to professional data analytics and business intelligence practice. It prioritizes orientation, essential tools, one clear workflow and a mentor-reviewed mini project. It is most suitable for beginners, students testing the domain, or course learners who need a short practical component.

Week 1 – Orientation and foundation: skill assessment, program rules, tool setup, task tracking, Excel, data cleaning and structured reporting and a short guided exercise.

Week 2 – Core practice: SQL querying and database basics, mentor demonstration, individual practice and a quality checklist.

Week 3 – Mini project build: apply statistics, KPIs and analytical thinking to a scoped project with milestone review and corrections.

Week 4 – Finalization: testing or quality review, documentation, presentation, mentor feedback and next-learning roadmap.

Expected 1-month evidence: One completed mini project, task log, project summary, mentor feedback record and final presentation. Example project: Excel MIS and performance report.

Option 2

3-Month Data Analytics Applied Internship

The three-month pathway is the recommended option for learners who want meaningful portfolio evidence. It combines a foundation phase, an applied phase and a capstone phase. Interns work on at least two guided assignments and one larger project, with regular reviews that focus on quality, documentation and problem-solving.

Month 1 – Foundation and workflow: Excel, data cleaning and structured reporting, SQL querying and database basics, statistics, KPIs and analytical thinking; tool setup; guided exercises; communication and documentation standards.

Month 2 – Applied delivery: Power BI or Tableau dashboard development, business case analysis and data storytelling, Python-based analysis with pandas; first project review; debugging, critique or analysis; iteration after feedback.

Month 3 – Capstone and portfolio: build Power BI executive dashboard or another approved project; complete testing, documentation, presentation and portfolio packaging.

Expected 3-month evidence: Two guided projects, one capstone, weekly progress records, review notes, final presentation and a portfolio-ready case study. Suggested project options include SQL sales analysis, Power BI executive dashboard and Marketing campaign analysis.

Option 3

6-Month Data Analytics Advanced Internship

The six-month pathway is intended for learners seeking deeper, sustained practical experience. It includes specialization, team workflow, quality assurance and a production-style capstone. Interns gradually take greater ownership while remaining accountable to scope, security, ethics and mentor review.

Month 1 – Foundation: Excel, data cleaning and structured reporting and SQL querying and database basics, baseline tasks and work standards.

Month 2 – Core build: statistics, KPIs and analytical thinking plus the first guided project and review cycle.

Month 3 – Applied specialization: Power BI or Tableau dashboard development and business case analysis and data storytelling with an intermediate project.

Month 4 – Integration: Python-based analysis with pandas and cross-functional workflow, documentation and quality checks.

Expected 6-month evidence: A structured portfolio containing three or more projects, an advanced capstone, documented iterations, mentor reviews, a presentation and a skills matrix. Suggested advanced projects include Marketing campaign analysis, Operations or inventory analytics and End-to-end BI capstone.

Skills and Tools

What Interns Will Learn and Practice

Foundation skills: Excel, data cleaning and structured reporting, SQL querying and database basics, statistics, KPIs and analytical thinking.

Applied skills: Power BI or Tableau dashboard development, business case analysis and data storytelling, Python-based analysis with pandas.

Advanced skills: data modelling, DAX and advanced SQL, automation, governance and quality checks, executive dashboard and analytics capstone.

Problem decomposition, requirement clarification and task estimation.

Professional communication, asking useful questions and reporting blockers early.

Documentation, version control or evidence management appropriate to the domain.

Quality assurance through testing, review, critique, validation or rehearsal.

Portfolio presentation that explains the problem, process, decisions, result and lessons learned.

Working Environment

Tools, Platforms and Working Environment

The exact stack may vary by batch and project. Typical tools include Microsoft Excel, Power Query, SQL, Power BI, DAX, Tableau, Python, pandas, GitHub, approved cloud spreadsheet or database. Skillonit should publish only the tools that are actually supported in the selected batch and provide setup guidance, access requirements and alternatives where paid licences are involved.

Project Practice

Live Projects and Portfolio Work

Real client projects are included only when an approved project, permission and review process are available; otherwise learners work on realistic industry simulations or mentor-designed capstones.