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#1 Data Analytics Institute

Data Analytics Course

No.1 Data Analytics Institute with Proven Placement Assistance

Study Giant Academy Study Giant Academy — Industry-Certified Training, Open to Learners From Anywhere
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Making Sense of Data —
Learn Data Analytics

Every company you can think of is sitting on more data than they know what to do with. The problem isn’t data — it’s people who can make sense of it. That gap is exactly what a data analyst fills, and it’s why the demand for this role has held up even when other tech hiring has slowed.

Our Data Analytics course at Study Giant Academy is built around that reality. We don’t just teach you Excel formulas or how to build a dashboard. We teach you how to look at a dataset, ask the right questions, and come back with answers that actually help a business decide something.

Most people who join aren’t from a technical background — and that’s fine. Our data analytics training is designed to take you from beginner to job-ready, not just tool-familiar, wherever you’re joining from.

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Data Analytics Training at Study Giant Academy

Why Data Analytics is a Strong Career Choice Right Now

The IT sector has always had a strong presence, but analytics hiring has expanded well beyond IT into finance, healthcare, logistics, e-commerce, and manufacturing. Companies that never used to think about data now have dedicated analytics roles — and they’re struggling to fill them.

What the market actually looks like right now:

  • Entry-level data analyst roles are genuinely available to freshers — this is one of the few tech-adjacent fields where your degree matters less than your skills.
  • IT companies, MNCs, and product-based firms across major tech hubs consistently post analyst openings across the year.
  • Finance, banking, and BFSI companies have significantly increased analytics hiring over the past two years.
  • E-commerce and logistics companies regularly hire reporting and MIS analysts for their operations teams.
  • Salary range for entry-level data analyst roles is roughly ₹3.5L–5L; mid-level analysts with 2–3 years of experience can earn ₹7L–12L+.

What You'll Learn in This Course

The course follows the actual workflow of a working data analyst — from cleaning messy raw data to building dashboards that non-technical stakeholders can actually read and use.

Skill Area What It Actually Covers
Excel for Analytics Beyond basic formulas — pivot tables, VLOOKUP, data validation, and building reports that update automatically
SQL Writing queries to pull and filter data from databases — the single most-asked-for skill in analyst job listings
Power BI Building dashboards and visual reports that tell a story without the reader needing to dig through a spreadsheet
Python Basics Enough Python to handle data cleaning, automation, and basic analysis — not software engineering
Data Cleaning Dealing with missing values, duplicates, inconsistencies — the part of the job nobody talks about but everyone does
Business Analysis Translating a business question into a data problem, and a data answer back into a business recommendation
Case Studies Working through real datasets from industries like retail, finance, and logistics — the kind of thing you’d actually see on the job

Tools You'll Work With

We train on the tools that appear in real job descriptions — not academic alternatives, not outdated software. If you look at analyst job listings today, these are what you’ll see listed under requirements.

Tool What It’s Used For Why It Matters
Microsoft Excel Data manipulation, reporting Required in almost every analyst role
SQL Database querying The most-asked-for skill in analyst JDs
Power BI Dashboards, visualisation Dominant BI tool used by companies everywhere
Python (basics) Data cleaning, automation Increasingly expected even at junior level

Course Syllabus

Eight modules, structured to match the order in which a real analyst actually works through a project — not alphabetically, not by tool complexity.

M1 Data Analytics Foundations
  • What data analysts actually do day-to-day
  • Types of data and data sources
  • The analytics workflow from raw data to insight
M2 Excel for Data Analysis
  • Pivot tables and pivot charts
  • VLOOKUP, HLOOKUP, INDEX-MATCH
  • Data cleaning and validation in Excel
  • Building automated reports
M3 SQL for Data Querying
  • SELECT, WHERE, GROUP BY, ORDER BY
  • Joins and subqueries
  • Aggregate functions
  • Working with real databases
M4 Data Cleaning & Transformation
  • Handling missing and duplicate data
  • Standardising formats
  • Preparing data for analysis and reporting
M5 Power BI & Data Visualisation
  • Connecting data sources
  • Building interactive dashboards
  • DAX basics
  • Designing reports for non-technical audiences
M6 Python for Analytics
  • Pandas for data manipulation
  • NumPy basics
  • Data visualisation with Matplotlib
  • Automating repetitive tasks
M7 Business Analysis & Case Studies
  • Translating business problems into data questions
  • Real dataset projects across industries
  • Presenting findings clearly
M8 Portfolio & Career Preparation
  • Building an analytics portfolio
  • Resume optimisation for analyst roles
  • Interview prep: technical and business questions
  • Placement support

You’ll complete the course with a portfolio of real analytics projects dashboards, SQL queries, and case studies you can walk an interviewer through.

Who Can Join This Data Analytics Course?

The short answer: most people. We’ve had BCom graduates, engineers, finance professionals, HR managers, and complete career switchers go through this course and land analyst roles. What they had in common wasn’t a technical background — it was a willingness to actually work through the material.

  • Fresh graduates from any stream — BCom, BBA, BSc, BTech. Your degree field matters less than your ability to think through a problem.
  • Working professionals who want to move into analytics from their current domain — finance, operations, HR, and sales people all make strong analysts.
  • Accountants and finance professionals who already understand business numbers and want to scale that with data tools.
  • IT professionals who are comfortable with systems but want to shift toward the data and analytics side.
  • Career switchers — we’ve placed people who came from teaching, retail management, logistics, and customer service roles into data analyst positions.

No coding background needed. The Python module starts from scratch, and SQL is taught as a language — not as programming.

What's Different About Data Analytics Training at Study Giant Academy

There are several data analytics institutes out there. The difference in outcome usually comes down to one thing: whether the training is built around getting you a job, or just getting you through a syllabus.

As a data analytics institute with a specific focus on placement outcomes, our approach is different from the start. Our trainers have worked as analysts — in actual companies, on actual business problems. They know what interviewers test for, what tools hiring managers actually care about, and where freshers tend to struggle in the first few weeks on the job.

Data analytics classes that focus on portfolio work and real datasets consistently produce better-placed graduates than those that teach tools in isolation. That’s the approach we take.

What We Offer What It Means for You
Trainers with real analyst experience They’ve done the job, so they teach what actually matters — not just what’s in the textbook
Real datasets from day one You’re not working through dummy data — you’re dealing with the kind of messy, real-world datasets analysts actually face
Project and portfolio focus Every project is built so you can present it in an interview — not just tick a module completion box
Small batch sizes Enough space to get actual feedback on your work rather than generic correction
One-on-one mentorship Direct guidance on where your analysis is going wrong, not just ‘try again’
Placement assistance Resume prep, interview coaching, and referrals to the companies we work with regularly

How the Training Works — Step by Step

We don’t hand you a course outline and expect you to follow it independently. Here’s how your journey actually looks:

1 We start with a conversation about your current background, what kind of analyst role you’re aiming for, and whether there are specific industries you want to work in. That shapes how we frame the training.
2 Excel and SQL foundations — covered practically, with real data from the first session rather than feature walkthroughs on clean demo files.
3 Data cleaning and transformation work — because this is where most junior analysts spend a surprising amount of their time, and most courses skip it.
4 Power BI dashboard projects — you’ll build dashboards that connect to real data sources and are designed for a non-technical audience to actually use.
5 Python for analytics — we cover what’s actually useful for an analyst: Pandas for data work, basic automation, and visualisation. Not software development.
6 Business case studies across different industries: retail sales analysis, financial reporting, logistics performance, marketing funnel data — the kind of projects that come up in interviews.
7 Portfolio review and resume preparation — your trainer helps position your projects in a way that makes sense to a hiring manager reviewing dozens of analyst applications.
8 Placement support: interview coaching, referrals, and connections to the companies we’ve placed analysts with before.

Where This Course Can Take You

Data analytics opens up more role types than most people expect going in. The skills you build transfer across industries, which is one of the things that makes it a solid long-term career choice.

Role Common Industries Core Skill Used
Data Analyst IT, BFSI, E-commerce SQL, Excel, Power BI
Business Analyst Product companies, Consulting Business analysis, reporting
Reporting Analyst Finance, Operations, MNCs Excel, Power BI, dashboards
MIS Analyst BFSI, Logistics, Retail Excel, reporting automation
Junior Data Scientist Tech companies (with extra learning) Python, statistical basics

Our Data Analytics Training Centre

Our Data Analytics Training Centre welcomes learners from anywhere — whether you’re based nearby or joining from a completely different city or country. You don’t need to relocate or be local to take this course.

For students who can’t attend in person, or those balancing full-time work commitments, we offer the same course fully online: live trainer-led sessions, the same curriculum, and full placement support, no matter where you’re located. We offer flexible learning options including weekday, weekend, and fast-track batches to suit different schedules. For those who are unable to attend in person due to distance or work commitments, we also provide a complete online Data Analytics program with the same trainers, course structure, and support.

Open to Learners Anywhere

No need to relocate or be local to take this course.

Online & Offline Paths

Flexible weekday, weekend, and fast-track batches available online and offline.

Frequently Asked Questions

How long does the data analytics course take?

The data analytics course duration is typically 2 to 3 months, depending on the batch type. Weekend batches run a little longer; fast-track options are available if your schedule requires it.

Do I need to know coding or have a technical background?

No. The course starts from scratch on all tools including Python. If you’ve never written a line of code, that’s a normal starting point for our students — not a disadvantage.

How quickly can I expect to get placed after completing the course?

Most students start receiving interview calls within 30–60 days of finishing. Our placement cell connects you with our hiring network and preps you specifically for the roles you’re applying to.

Which tools will I have learned by the end of the course?

Excel, SQL, Power BI, and Python basics. These are the four tools that appear most consistently in entry-level data analyst job listings right now.

Can I do this course online from anywhere?

Yes. The full program is available online with the same trainer and the same placement support. We have students joining from across the country and beyond.

Is data analytics a stable career path or just a trend?

It’s genuinely stable. The underlying need — companies making decisions based on data — isn’t going away. If anything, demand has grown as more industries outside IT have started building analytics functions.

Ready to Start Your Data Analytics Career?

Book a free demo session with us. If you’ve been searching for data analytics training that builds real job skills — not just tool familiarity — come and see how we approach it. No pitch, no pressure, just an honest conversation about what’s right for you.

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Get in Touch with Our Design Experts

Have questions about the course, batch timings, or placement statistics? Fill out the form, and our career counselors will get back to you within 24 hours.

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