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DATA ANALYTICS · CAREER TRACK

Turn raw data into answers people can use.

Learn to clean a table, investigate a question and build reports that make business activity understandable. Good analytics connects a number to a definition, a source and a useful decision.

Enquire about this trackIs it for me?

₹30,000 per level including GST · Level 1 has no prerequisite · optional Career Audit

A portfolio you can explain

Sales performance dashboard

Help a fictional retailer understand which products and regions changed sales.

Illustrative output: A dashboard, calculation dictionary and reconciliation sheet.

Explore the project briefs →
THE SHORT ANSWER

What is Data Analytics as a career track?

Data Analytics is a mentor-led career track. Its focus: Answer business questions with SQL, spreadsheets and dashboards. First roles to search for include Data Analyst Trainee, Business Analyst Trainee, MIS Executive. Level 1 takes 3 months at ₹30,000 including GST, with no prerequisite. Coding: Spreadsheets to start; SQL is valuable for querying data.

WHO THIS TRACK SUITS

Is Data Analytics right for you?

People who like answering a concrete question with data and presenting it clearly. It is the most accessible track for someone starting from zero.

Students
The most common first track. SQL, spreadsheets and a dashboard are learnable from zero, and you finish with something to show.
Freshers
Prepares you directly for data analyst, MIS and reporting roles: the first project is the kind of dashboard those roles build.
Working professionals
Fits finance, sales, HR and operations people who already live in spreadsheets and want to answer their own questions with SQL and a dashboard.
Look elsewhere if
If your interest is in business decisions and requirements more than the data preparation, look at Business Analytics. If you want models, look at Data Science.
Coding
Spreadsheets to start; SQL is valuable for querying data.
Mathematics
Percentages, averages, rates and distributions.
Before you start
Practise sorting, filtering and simple spreadsheet formulas. Learn what one row represents and how dates and missing values behave.
WHAT YOU WILL WORK ON

What will you learn in Data Analytics?

You learn these areas from recommended external courses; your mentor sets the practice and reviews the work.

1

Data preparation

Organise raw records into consistent tables for analysis.

2

Analysis and reporting

Summarise activity and investigate changes across groups or periods.

3

Dashboards

Present the relevant measures and filters for a business question.

4

Business insights

Explain findings, qualifications and next questions through a report.

TOOLS AND SETUP

What tools do you need for Data Analytics?

SQL (a free database on your laptop), a spreadsheet, and one business-intelligence tool for dashboards. All available free for learning.

MENTORSHIP & REVISIONS

Bring your thinking to the review.

Review definitions and source totals before chart styling. Check duplicate rows, join behaviour, date filters, denominator choices and whether the dashboard answers a specific question.

See a sample review round →
LEVELS IN THIS TRACK

How long does Data Analytics take, and what does each level add?

Level 1 (3 months): small assignments and your first Data Analytics project, reviewed until it holds up. Level 2 (6 months): one larger project with revisions; resume review and mock interviews begin. Level 3 (6 months): a bigger project, portfolio guidance and application guidance for the roles you choose. Level 4 (6 months): a multi-part project with 1-on-1 reviews and system design and architecture review; aimed at working professionals switching direction. Every level is ₹30,000 including GST, bought one at a time.

What each level includes →
PRACTICE WITH PURPOSE

What projects will you build in Data Analytics?

Illustrative briefs set by mentors for practice, built on synthetic or appropriately licensed data. Your mentor sets your actual project to fit your level.

Illustrative project 01

Sales performance dashboard

Help a fictional retailer understand which products and regions changed sales.

Sample inputs
Synthetic orders with order ID, date, region, product, quantity, price and refund status.
Your tasks
Define net sales, clean duplicates, aggregate by period and build filters with a concise findings memo.
What to deliver
A dashboard, calculation dictionary and reconciliation sheet.
Quality checks
A duplicated order must not increase totals; refunded orders and incomplete periods need explicit treatment.
Interview discussion
Explain why growth in revenue may not imply growth in profit.
Illustrative project 02

Support response report

Find where support tickets wait longest.

Sample inputs
Fictional tickets with received time, first response time, category and status.
Your tasks
Calculate elapsed time, segment by category, examine long waits and separate open tickets.
What to deliver
A service report with median and tail response times.
Quality checks
Handle time zones, missing responses and negative durations; do not silently discard unfinished tickets.
Interview discussion
Explain why the average alone can hide a poor experience for some users.
Illustrative project 03

Campaign analysis notebook

Compare marketing outcomes without confusing clicks with purchases.

Sample inputs
Synthetic campaign spend, clicks and attributed orders with a declared attribution rule.
Your tasks
Calculate conversion and cost metrics, compare cohorts and present two follow-up investigations.
What to deliver
A campaign dashboard and a one-page limitations note.
Quality checks
Use consistent denominators, distinguish orders from customers and avoid causal claims from observational data.
Interview discussion
Explain how changing attribution rules would change the recommendation.
FIRST ROLES, HONESTLY

What jobs can Data Analytics lead to?

Data analyst, MIS and reporting roles are among the most accessible entry points in Indian tech hiring, and they are the first roles this track prepares for. Employers look for SQL, a BI tool and the habit of checking a number against its source.

Preparing recurring reports, checking data quality, maintaining dashboards and answering operational questions. Explore reporting analyst, MIS executive and data analyst trainee roles.

We do not guarantee eligibility, interviews or employment.

YOUR PORTFOLIO

Make your contribution visible.

A cleaned dataset, documented queries or formulas, a dashboard and a short findings memo with source reconciliation.

Career preparation by levelAll project briefs
PRACTISE THE CONVERSATION

What you will be asked about this work.

The questions attached to each project brief are the ones a mentor asks in review and an interviewer asks later. From Level 2, you rehearse them in mock interviews.

  1. 1

    ABOUT “SALES PERFORMANCE DASHBOARD”

    Explain why growth in revenue may not imply growth in profit.

  2. 2

    ABOUT “SUPPORT RESPONSE REPORT”

    Explain why the average alone can hide a poor experience for some users.

  3. 3

    ABOUT “CAMPAIGN ANALYSIS NOTEBOOK”

    Explain how changing attribution rules would change the recommendation.

QUESTIONS ABOUT THIS TRACK

Before you choose Data Analytics.

Can I start without a CS degree?

Yes, spreadsheet practice and numerical reasoning are useful starting points. Check the programme's preparation requirements with the team.

Do analysts need SQL?

SQL is widely useful for retrieving and summarising structured data. It complements spreadsheets and dashboards.

Is Data Analytics the same as Data Science?

Analytics commonly centres on questions and reporting. Data Science often adds statistical investigation and predictive modelling.

Is a colourful dashboard enough?

No. Define measures, reconcile results and make the intended decision clear.

What if my dataset has missing values?

Investigate why values are missing and document your treatment; automatically replacing every missing value with zero can distort results.

Can I use company data in a portfolio?

Only with appropriate permission and handling. Synthetic or openly licensed datasets are safer for public examples.

Which dashboard tool is guaranteed?

The projects use one free business-intelligence tool, agreed with your mentor at the start; the goal is sound reporting, not a particular product. If you already use a tool at work or college, you can usually keep it.

What should I explain in an interview?

Describe the question, data checks, calculations, insight and one limitation that could change your conclusion.

KEEP EXPLORING

Guides to read alongside Data Analytics

BY CITY

Where is Data Analytics a good fit?

These cities have employers that hire for the roles this track leads to.

Take your next step in Data Analytics.

Enquire about this track. The team calls you back, usually within one working day, to confirm the starting level.

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