How to Become a Data Analyst: Career Path, Opportunities, Salary, Scope

A career as a data analyst is a great idea for those who love numbers. From degree required to salary range to top colleges, Analytics professional Surjeet Singh shares how to become a data analyst in India.

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1. Role of a Data Analyst

Every business collects data, from shopping websites to media companies. This data includes logistics costs, consumer research, sales figures, websites’ visitor profiling and more. The main job of a data analyst is to fetch information from the raw data that will be of great use to their clients. Big data is a term that means a large a collection of data. This is structured, analyzed and interpreted to solve business problems, or interpret patterns and trends that can help a business.

I am an Analytics Professional and my technical skills include coding and analysis using various analytical tools like SAS, SQL, Python, R and Tableau. These tools help data analysts make sense of the raw data, to help companies understand their customers’ needs and ultimately, increase profits.

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Contents: Jump to Section

1.1 Difference between Data Analyst vs Data Scientist vs Data Engineer
1.2 Is Data Analytics a Good Career
2.1 Courses Taken: Data Analytics Subjects
2.2 Entrance Exams
2.3 Academic Qualifications/ Options
2.4 License Required
2.5 Internship/ Work Experience Required
2.6 Cost of Tuition and Training
2.7 Competition & Big Data Scope in India
2.8 General Age to Start Professional Career for Data Analysts
2.9 Governing Bodies
3.1 Specializations/ Sub-Professions
3.2 Companies & Institutions That Employ Data Analysts
3.3 Growth Prospects
3.4 Entrepreneurship Opportunities
3.5 Salary Range
4.1 Top Universities in India
4.2 Top Universities in World
4.3 Famous Personalities
4.4 Useful Links

1.1 Difference between Data Analyst vs Data Scientist vs Data Engineer

Data professionals are of different types:

  • data analysts
  • data engineers
  • data scientists
  • data architects
  • database managers
  • database administrators

You can also call them different data science paths.

Out of these, data analysts and data scientists have somewhat similar roles. A data analyst’s main role is to structure, analyze and interpret raw data, in order to provide solutions to a company’s questions, or find trends, etc.

Data scientists have a similar role as data analysts. However, they use machine learning models, or algorithms, and statistics to do so. And data engineers are the professionals who develop the software used by data scientists and analysts. They build, monitor, test and optimize the platforms or systems for data storage and analysis.

big data career path

1.2 Is Data Analytics a Good Career?

Yes.

Data analytics career paths are gaining a lot of popularity and respect these days, since many large corporations collect big data. So there is a lot of demand for all types of data professionals. Data analysts also considered intellectual, new tech professionals. All these factors, along with a good salary makes data analytics a good career choice.

2. How to Become a Data Analyst

2.1.1 Courses Taken at School

Science stream (PCM) with physics, chemistry, maths, computer and English.

You need to have a background in maths in 10+2 (high school) with an interest and aptitude for statistics.

Role of a Data Analyst

2.1.2 Courses Taken at College: Data Analytics Subjects

Here are some of the courses or subjects that are a part of B.Tech. in Computer Science (see Section 2.3.1), which can be a helpful background for a career in Data Analytics:

  • Data Structures
  • Digital Logic Design
  • Design and Analysis Of Algorithms
  • Data Base Management Systems
  • Computer Programming
  • Object Oriented Programming using C++/Java/Python
  • Digital Electronics
  • Theory of Computation
  • Discrete Mathematical Structures.
  • Operating Systems
  • SQL, Python

2.2 Entrance Exams

Depends on the degree you go for – B.Tech is a good idea (see Section 2.3.1).

  • For engineering, JEE mains for IITs, Graduate Aptitude Test in Engineering (GATE) for others for undergrad college.
  • For B.Sc., some universities look for cut-off percentage in 12th, and others have internal qualifying exam or admission test.

Entrance exams for master’s degree are as follows:

  • CAT, CMAT and NMAT for MBA in India.
  • SNAP (for Symbiosis institutes) for MBA in India.
  • GMAT for MBA in the US and some other countries.

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2.3.1 Academic Qualifications/ Degree Required

Graduation required, especially B.Tech. Organizations have recently been emphasizing on B.Tech and/or MBA. 

As of yet, there is no undergraduate degree program for Data Analytics (by a recognized university). There are few certificate/ diploma courses by various institutes (like IIM, IIT, ISB) for graduates or working professionals.

So the best idea is to earn a bachelor’s degree (B.Tech or B.E.) in Computer Science, Information Technology or Statistics. And study applied statistics or data analysis as subjects within those, or do a certificate program.

I did B.Sc and MBA.

2.3.2 Post-Graduate Degree Requirements/ Options

MBA, Ph.D in a science-related field.

Most large organizations that hire data professionals prefer candidates with MBA degrees. After that, a Ph.D. in a science or statistics field could be an option for further studies, although it is not required. A Ph.D. would be a great idea if you want to become a data scientist.

Some universities abroad also offer degrees like Master of Science in Analytics or Master of Science in Data Science. But it is better to get experience in data analytics before going for (or considering) these masters degrees, since job experience will help you gain understanding of the field and interdisciplinary knowledge. Sometimes, it may even be a better idea to avoid masters in analytics and go for an MBA instead, as a lot of companies prefer that. So getting work experience in the field will help you understand the employers’ demands and preferences.

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2.4 License Required

No.

2.5 Internship/ Work Experience Required

Yes.

Internship depends on what degree or course you go for. A 6-month internship is a part of the B.Sc programs. For B.Tech or B.E., internships are required. Students typically join an internship in summer holidays, usually for 3 months between 3rd and 4th year of college.

It is highly desirable to find an internship in data analytics or data science, depending on your interest or chosen career path.

For Ph.D., to enter the program, you must work in a laboratory during college/university, including summers, as well as write a senior research thesis.

2.6 Cost of Tuition and Training

For B.Tech or B.E, approximate fees at NITs is around INR 5 lacs for a 4 year course, which excludes hostel fees. Total spend should be around INR 7-8 lacs, including hostel.

Students should note that there is a vast difference in tuition in private and government engineering colleges. Good private engineering colleges have fees of about 3 lacs per year for a 4 year course, which makes a total of about 12 lacs, excluding hostel.

For MBA, top colleges charge anywhere between 5-8 lacs for a 2 year course, excluding hostel. Total spend will be around 10-12 lacs.

big data analyst science career path roadmap skills

2.7 Competition & Big Data Scope in India

Highly competitive for college entrance. Less competitive for jobs.

Getting into a good college and university will account for the most of the competition you will face. Competition will depend on the ranking of college, and the better the college, the higher your chances at getting a job and better salary.

Getting into IITs and government colleges is quite tough, as you’ll be competing with the top students of the country. Try to get into a good school and a top B-school as they have the best companies visit during campus placements.

To get into the top colleges, start your preparations early for entrance exams. For B.Tech, you should start as early as in 10th grade and for MBA/MS, as early as 3rd year of a 4 year graduation or 2nd year of a 3 year graduation.

For jobs, the competition level is moderate, although it may increase in the coming years, due to the increasing popularity of this career option among young graduates. If you graduate from one of the top colleges, it should be fairly easy to land a good entry-level job either through college placement or online applications. Demand for data professionals is increasing year after year, so it seems like a secure career choice in the coming technological era.

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2.8 General Age to Start Professional Career for Data Analysts

23-24 years.

Since analytics is relatively new field, earlier the companies used to hire candidates with MBA and experience (25-30 years) for data analysis. But now freshers are also being hired.

2.9 Governing Bodies

None.

3. Professional Opportunities/ Career Growth for Data Analysts

3.1 Specializations/ Sub-Professions

Data professionals are of different types:

  • data analysts
  • data engineers
  • data scientists
  • data architects
  • database managers
  • database administrators

However, under data analytics, there are no sub-professions. Data analysts may have certain specializations, such as market data analyst, web data analyst, IoT (internet of things) data analyst.

How to Become a Data Analyst in india qualifications salary skills

3.2 Companies & Institutions that Employ Data Analysts

Mostly private companies (consulting/BFSI /IT firms).

Banking, financial services and insurance (BFSI) and IT firms are the top employers of data analysts. Examples include Accenture, Barclays, J.P. Morgan, IBM, etc.

Other than that, large corporations and tech companies like Google, Amazon and Apple also hire data analysts. Consulting firms and data analysis companies like McKinsey, Boston Consulting Group (BCG), TCS, Bloomberg, etc. also employ data analysts.

3.3 Growth Prospects

Certainly depends on the hierarchy system in the organization one in working for.

Data analysts can start as Data Analyst interns. Fresh graduates can get the position of Data Analyst, and then be promoted as Senior Data Analyst after 2-4 years of experience. Other senior positions include Lead Knowledge Analyst, Knowledge Expert, Data Analytics Consultant, Head – Global Data & Analytics and Vice President – Business Data Analyst.

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3.4 Entrepreneurship Opportunities

Yes.

In the recent years, a number of start ups have come up. Gurugram, Bengaluru and Hyderabad are the main hubs for startups and entrepreneurial ventures for data analysts. Data analysts can start their own consulting firms to provide solutions to clients based on data visualizations & analysis.

Analytics startups can provide SaaS (software as a service). They develop machine-learning software and advanced analytical applications for big data analysis. These tools or software can provide solutions for collecting, storing, cleaning or analyzing data.

3.5 Salary Range

On an average its ₹4-5 lacs per annum for freshers.

A good college fresh B.Tech graduate can get anything above ₹6 lacs p.a., especially with a masters degree. After 1-2 years experience, it is common for data analysts to earn ₹5-5.5 lacs p.a.

4. Further Resources

4.1 Top Universities in India

Few IIM institutes (like Lucknow and Ahmedabad) are the top colleges when it comes to diploma course in Big Data/ Analytics. Additionally, IIT Hyderabad offer diploma course in Big Data/ Analytics for working professionals. Various MBA colleges in India have starting specific big data/analytics programs.

But I would suggest to go for a normal MBA course from a good institute as it would cover things one needs in this field. And yes, good institutes can promise job interviews.

For:

B.Tech – All IITs, All NITs

MBA – All IIMs, SPJIMR, SCMHRD, NMIMS, JBIMS, XLRI

4.2 Top Universities in World

  • Harvard University (Master of Science in Data Science)
  • Massachusetts Institute of Technology (MIT Sloan) (Data Analytics Certificate)
  • Carnegie Mellon University (Master of Science in Information Technology with a specialization in Business Intelligence & Data Analytics)
  • Penn State University (Master in Data Analytics; Master of Professional Studies in Business Analytics)
  • Boston University (Master of Science in Computer Information systems)
  • Missouri University of Science and Technology (online graduate certificate in Business Analytics and Data Science)
  • Illinois Institute of Technology, Chicago (Master of Data Science)
  • Johns Hopkins University (MS in Data Science; post-master’s certificate in Data Science)
  • UC Berkeley, California (Master of Information and Data Science)

For top universities in the world for MBA, please refer Section 4.2 in Business Management.

4.3 Famous Personalities

  • Kenneth Cukier
  • Dean Abbott
  • Hilary Mason
  • Geoffrey Hinton
  • Bernard Marr

4.4 Useful Links

Internet is full of helpful videos for Analytics field aspirants. One can check the website for SAS. Its an US based organization which developed the initial analytic tool (SAS).

Read next:

Is Data Analyst a Good Career for You? All About Big Data Career Path

Is data analyst a good career for you? From challenges to what being a data analyst will be like on a daily basis, Analytics professional Surjeet Singh discusses everything about the big data career path.

3 thoughts on “How to Become a Data Analyst: Career Path, Opportunities, Salary, Scope”

  1. If you want more job opportunities, try going for an advanced degree. Employers are looking for candidates that have knowledge in the latest technologies and tools. A master’s degree in data science, data analytics or big data management is a good choice. Learn the the newest software programs and do an internship. These degrees will expose you to team assignments, internships, & projects designed by experts to help you gain invaluable real world experience in college.

  2. You actually make it seem so easy but data science is actually something that I think I would never understand.
    It seems too complex for me.

  3. Amazing Blog. thank you for sharing this information. Data analytics course is an interdisciplinary field that combines elements of mathematics, statistics, computer science, and domain knowledge to extract insights and knowledge from structured and unstructured data.

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