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Can A BBA Student Do Data Science – A Complete Guide

BBA and data science look poles apart, but that’s not the case.

It may surprise you, but you can take a data science course after completing your BBA. In the real world, most BBA graduates take up data science as a preferred career option.

If you are wondering how this is possible, here are a few facts that make it possible:

  1. Data science does not belong exclusively to tech grads. With a few requisites and skills, you can also be an expert in data science.
  2. Data science requires analytical skills. BBA graduates have already honed their analytical skills, allowing them to think strategically and strengthen their problem-solving skills.
  3. A BBA graduate already understands the science of statistics and business information, which comes in handy while studying data science.

Now, without further ado, let’s dive in further to understand how a BBA student can learn data science.

What is BBA?

BBA stands for Bachelor in Business Administration. It is one of the most pursued courses among students after 12th grade. The tenure of this course is three years and opens a doorway to several key sectors, such as education, finance, marketing, and sales, to name a few.

There’s a constant surge in demand for BBA courses. The course enables the students to gain in-depth knowledge of the managerial skills required to operate a business efficiently. The course equips the student with business administration and marketing skills.

In addition, the course develops management and leadership skills, preparing the trainee to take on managerial roles. As a result, the trainee gets more clarity on the various stages of business and techniques to run it smoothly.

Students from any stream, such as the arts, science, or commerce, can pursue BBA graduation. BBA can be done full-time for three years via campus education, correspondence, or online.

It’s possible to do a BBA with the following specializations:

  1. Marketing
  2. Sales
  3. Supply Chain and Analytics
  4. Digital Marketing
  5. Finance
  6. Business Analytics
  7. International Business
  8. Operations
  9. Human Resources
  10. Retail Management
  11. Data Analytics

What is Data Science?

Today, businesses have come a long way and are exploring innovative ways to excel. One of the ways is to study the data and derive valuable and meaningful insights for business, also known as ‘Data Science’.

Data science involves analyzing large amounts of data by combining principles and techniques from artificial intelligence, computer engineering, mathematics, and statistics.

The analysis further helps businesses seek answers to questions, such as what happened in the past, why it happened, and what will happen in the future, along with what they need to do with the results.

Data science has gained immense importance today. It opens several doors to understanding where the world is going, as it generates meaningful wisdom from the available data.

Today, modern devices help accumulate data by capturing details. These devices capture data in the form of audio, video, images, and text.

Data processing has acquired a faster pace; thanks to innovations like artificial intelligence and machine learning technologies. As a result, the demand for data scientists is also surging continuously, which has given rise to various courses and degrees offering training in data science.

Data science demands cross-functional skillsets and expertise, which makes it a more demanding career with a decent package and lots of growth opportunities in the future.

How Can a BBA Student Become a Data Scientist?

Well, a BBA student becoming a data scientist is possible. However, the student needs to put in extra effort to get there. An individual with reasonable mathematical or statistical skills can enjoy the ride to becoming a data scientist. But it won’t be so easy for the general population.

Therefore, for a BBA student to walk on the path to becoming a data scientist, here are a few steps that one can follow:

1. Training in programming languages

The main programming languages used for data science are R, Python, and SAS. Acquiring skills in any of these languages enables you to clean, exploit, and analyze data. Python for Data Science is easy to learn, according to most of the public opinion. However, you can start with the one you find easiest.

2. Learn to play with databases

Data science involves a lot of playing with databases. Learn how to extract data from SQL or Hadoop databases. A thorough practice with CRUD (Create, Read, Update, and Delete) will help you get comfortable with databases. Use HackerRank, Coderbyte, CodeChef, Geekforgeeks, and similar websites for practice.

3. Excel

MS Excel is one of the most popular applications on the planet. It’s an excellent tool that helps us create reports in attractive and visually appealing formats. Practice a lot in Excel to understand how to build reports in various ways.

4. Learn Tableau

Data scientists use visualization tools. One of the tools is Tableau. There are also alternate tools, but Tableau is the most popular. Most training institutes train on this tool. Therefore, getting help and guidance on this tool is easy if you get stuck anywhere while learning.

5. Statistics

Statistics is an uncommon subject. Therefore, one needs to learn it devoutly. Data science demands a basic knowledge of statistics. Google sites that offer training in statistics. Focus on the following concepts that will help you in your data science profession:

  1. Chi-Square Test
  2. Dispersion of data, Bell curve
  3. Hypothesis Testing
  4. Mean, variance, and standard deviation
  5. Measures of central tendency (mean, median, and mode)
  6. Percentiles of Data Distribution (First Quartile, Second Quartile, Third Quartile)
  7. The descriptive method and the inferential method

6. Models and algorithms

A data scientist needs to be well-versed in models and algorithms. Therefore, a basic understanding of models and algorithms regarding classification, clustering, regression, etc., makes the way to becoming a data scientist easy.

A few crucial examples are K-means, linear regression, logistic regression, and SVM.

7. Soft skills

Soft skills such as communication and creative thinking are vital. Unless you are proficient in these skills, you won’t be able to explain your research effectively. You need to think outside the box and give a new perspective to your findings.

Also Read: How to Switch Your Career From Software Testing to Data Science

Effective Tips For Beginners to Learn Data Science After BBA

  1. You can either pick a free data science course or start learning data science from Youtube
  2. Once comfortable with a programming language, you can invest in a training course on portals offering paid courses, such as Coursera, Udemy, SimpliLearn, etc.
  3. Check out datasets and codes developed by other developers on GitHub or Kaggle. Self-study those and try to replicate the same on your own.
  4. You can either self-learn the basics of data science or join a reputed institute that offers classroom training in data science.
  5. Self-learning is excellent for the self-driven, self-motivated, and outrageously disciplined. However, when you join an institution, peer pressure and knowledge sharing make the journey of learning anything enjoyable and quick.
  6. Subscribe to some of the best Data Science YouTube channels, forums, and blogs discussing data science trends.
  7. Apply for a data science course that is close to your favorite niche.
  8. Data science requires vigorous work. Try to immerse yourself in the learning process as much as possible to become an expert.

Also Read: Top Tech Skills In Demand For Career


A BBA graduate can become a data scientist. There are many institutions offering data science training for BBA graduates. Some institutions have combined the BBA and data science and introduced a BBA in the Data Science course. It will surely save a few years for the individual.

Learning data science requires effort from the candidate’s side. It requires learning programming languages, databases, visualization techniques, and general soft skills to succeed as an expert in data science.

Data science is one of the hottest career options, paving the way for a decent career path. So, what are you thinking?

Start learning Data Science and begin your career journey as a Data Scientist.

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