Data Analyst

Cleaning messy data, writing SQL queries to pull figures, building Power BI or Tableau dashboards, and writing short reports that explain what the numbers mean for managers.

A day in the work
Many mornings start with checking whether the overnight data refresh worked and whether any figures look wrong. Then you write SQL queries to pull the sales, customer or cost numbers a team has asked for. Afternoons often go to updating a Power BI or Tableau dashboard and checking it against the raw data. You end the day with a short call or email to explain to a manager what the numbers show and what they might mean.

1. Step 1 · Class 11–12Choose any stream. Take Maths or Statistics if you can, and practise Excel formulas and pivot tables. Computer Science or Informatics Practices is a useful early start.
2. Step 2 · Graduation (about 3 years)Take any bachelor's degree. Computer science, statistics, economics and commerce are common choices, but no one subject is compulsory. (reported — check with the official body)
3. Step 3 · Second and third yearLearn Excel well, then SQL, then one dashboard tool such as Power BI or Tableau. Python with pandas is increasingly asked for, so add it when you can. (reported — check with the official body)
4. Step 4 · Final yearBuild three or four small projects on public datasets and put them online. For each one, write a short note on what the finding meant for a decision. (reported — check with the official body)
5. Step 5 · After graduationApply for junior analyst or MIS roles at IT services firms, banks, e-commerce companies and analytics consultancies. Expect an Excel or SQL test at interview. (reported — check with the official body)
6. OptionalA master's in data science, statistics or business analytics can help with later promotions. It is not needed to start.

Fees from: NPTEL: Data Analytics with Python course page. Fees change every year — check the college's own fee page before you pay.

Pay varies a lot. Entry-level analysts earn much less than people with several years of work, and the city, the industry and the type of employer (IT services, product company, bank) make a big difference. Strong SQL, a dashboard tool and Python tend to raise offers.

• Class 7–9With a parent, look at the job profiles on the National Career Service portal and note which ones use numbers or data every day.Open link ↗
• Class 10–12Open the free NPTEL Data Analytics with Python course page and watch the first week's lectures. The certificate exam is optional.Open link ↗
• College or afterTake a small dataset from your own college or family shop, such as monthly sales, and make one Excel summary and one simple chart that answers a real question.

• No government licence or registration is needed. Employers decide who they hire, based on skills and projects.
• A certificate helps a little, but a small set of working dashboards and clear SQL answers usually counts for more in interviews.
• Government data roles exist, for example in statistical services and national IT bodies. They have their own exams and notices, so always read the official notice for the year.