Data Analyst

Career overview

Every organisation now collects far more data than it can easily read — every sale, click, delivery and customer complaint leaves a record. Data analysts organise that information and answer specific questions: Which products are selling less this quarter? Why are customers cancelling? Which branch is performing best?

The role sits between technology and business. It needs enough technical skill to work with databases and tools, and enough business sense to know which questions matter and how to explain the answers to people who are not numbers-minded.

What does a data analyst do?

A typical task starts with a question from a manager. The analyst finds the relevant data, often by writing database queries, cleans it (fixing duplicates, gaps and errors), and then analyses it with spreadsheets, statistics or code. The result is usually a chart, a dashboard or a short report with a clear recommendation.

Many analysts also maintain regular reports and dashboards that teams check daily or weekly, and they help design how data should be captured in the first place. With experience, analysts take on more open-ended problems, run experiments such as A/B tests, and advise leadership directly.

Typical work environment

Data analysts work in offices or remotely at IT and analytics firms, banks, e-commerce companies, consultancies, hospitals, government bodies and global capability centres. The work is desk-based and collaborative, with regular meetings with business teams. Hours are mostly regular, though month-end reporting and urgent leadership requests can create pressure.

Key responsibilities

• Understanding the business question behind a request
• Extracting data from databases and other sources using SQL and tools
• Cleaning, checking and organising data
• Analysing trends, patterns and exceptions using statistics
• Building dashboards and regular reports
• Presenting findings clearly to non-technical colleagues
• Suggesting improvements to how data is collected and recorded

Skills required

• Spreadsheets at an advanced level — formulas, pivot tables, lookups
• SQL for querying and combining data from databases
• Statistics — averages, distributions, correlation, sampling and basic testing
• Visualisation and BI tools for building clear charts and dashboards
• Python or R for larger or repeatable analyses (increasingly expected)
• Business understanding — knowing what the numbers mean for the organisation
• Storytelling with data — turning analysis into a clear, short message

Personal qualities that may help

• Curiosity about why numbers look the way they do
• Attention to detail and healthy scepticism about data quality
• Patience with repetitive cleaning work
• Ability to explain findings simply
• Objectivity — reporting what the data says, not what people hope for

School subjects that can be useful

• Mathematics, especially statistics and probability
• Computer Science or Informatics Practices
• Economics or Commerce, for business context
• English, for reports and presentations

Eligibility

• No single mandatory degree; most employers expect a bachelor’s degree
• Degrees with mathematics, statistics, computing, economics or commerce are the most common
• For analytics-focused degrees such as B.Sc Data Science, Mathematics at Class 12 is usually required — check each college
• Employers assess skills through aptitude tests, SQL/Excel tests, case studies and interviews

Courses and qualifications

Typical educational pathway in India

1. After Class 10Any stream can work, but choosing Mathematics in Class 11–12 keeps the widest range of degree options open.
2. Class 11–12Build comfort with maths and basic spreadsheets. Decide between technical, science and commerce degree routes.
3. Undergraduate degreeChoose a degree with a quantitative element — statistics, maths, computing, economics or commerce.
4. Learn the toolkitPractise SQL, advanced spreadsheets, a dashboard tool and basic Python using public datasets.
5. Build a portfolioComplete two or three analysis projects that answer real questions and explain the findings clearly. Internships help greatly.
6. First job and growthStart as a junior or MIS analyst, then grow towards senior analyst, analytics manager, or specialised paths such as data science or business analysis.

Career opportunities

• Data or MIS analyst in analytics and IT services firms
• Business intelligence analyst in banks, insurers and retailers
• Marketing, product or operations analyst in e-commerce and start-ups
• Healthcare, public-health and research data roles
• Analyst roles in consulting and market research firms
• Government and public-sector data projects

Industries that employ data analysts

• Banking, financial services and insurance
• E-commerce, retail and consumer goods
• IT services and analytics consulting
• Healthcare and pharmaceuticals
• Telecommunications and media
• Logistics and manufacturing

Entry-level roles

• Junior Data Analyst
• MIS Executive / MIS Analyst
• Reporting Analyst
• Business Intelligence Associate
• Operations or Marketing Analyst

Career progression and indicative salary

Salaries vary a lot by employer, city, industry and skill set; these are broad indicative ranges only.

Higher-study options

• M.Sc Statistics or Data Science for deeper technical skills
• MBA with a business analytics specialisation — see MBA / PGDM (Master of Business Administration)
• MS in Business Analytics or Data Science abroad
• Short professional certificates in specific BI or cloud data tools

Opportunities in India

Data analytics is used across Indian banking, retail, telecom, healthcare and government services, and demand for people who can work with data has grown steadily. Because the role is open to many degree backgrounds, competition at the entry level is high; a portfolio of genuine projects and strong SQL skills help candidates stand out.

In Hyderabad and Telangana, the IT and global capability centre cluster around HITEC City and Gachibowli employs many analysts in banking, insurance, healthcare and technology operations — see Global Capability Centres (GCCs) in Hyderabad: Careers for Students. Genome Valley’s pharma and life-sciences companies also need data skills for research and operations. Local students can reach these roles through B.Tech, BCA, B.Sc, BCom or BBA degrees, followed by focused skill-building.

International opportunities

Analytics skills are used worldwide, and a master’s degree in business analytics or data science abroad is a common route for Indian graduates. Remote work for overseas teams is also possible after gaining experience. Visa and work-permit rules change frequently, so check current official information before planning.

Advantages of this career

• Open to graduates from many streams, not only engineering
• Used in almost every industry, so options are wide
• Direct impact on real business decisions
• Natural stepping stone to data science, product or business roles
• Tools can be learnt affordably through practice and public data

Challenges to consider

• Crowded entry level with many short-course graduates competing
• A lot of time goes into cleaning messy data
• Findings are sometimes ignored or questioned by stakeholders
• Routine reporting is increasingly automated, so analytical thinking must deepen
• Tools change, so ongoing learning is needed

Is this career a good fit for you?

Compare this role with Data Scientist if you are interested in machine learning and more advanced modelling.

Future outlook

Organisations continue to rely on data for decisions, so analytical skills are expected to stay in demand. At the same time, AI and self-service tools are automating basic report creation, which means analysts increasingly need to frame good questions, judge data quality and explain what results mean.

Analysts who combine technical skills with deep knowledge of a domain — finance, healthcare, marketing, supply chain — are likely to have the most durable careers.

Frequently asked questions