Should I study business analytics or data science?
Business analytics and data science may seem like similar job roles at first glance, but there are many differences between the two. A degree in either will teach you the basic fundamentals to get you started on your career, but depending on your personal interests and ambitions, you may prefer one degree over the other. So, what is the difference between data science and business analytics? Let’s find out.
What is business analytics?
Business analytics is all about finding ways to improve a business. Although the medium has changed throughout the years, business analytics as a concept has been used since the late 19th century. Through the use of data and statistics, a business analyst will solve the problems a business faces in a logical and analytical way.
Business analytics may include analysing company data, forecasting from historical data, optimisation to improve strategies, or improving data visualisation through graphs and charts. Not only will you be analysing all of this data, but you will be responsible for sharing your findings with other employees in your company – supporting them in making the changes you’re suggesting.
What is data science?
Data science follows a similar principle to business analytics, but is much broader. The term was coined in 2008, by DJ Patil and Jeff Hammerbacher when working for LinkedIn and Facebook respectively. Much like business analysts, data scientists use data and analytics as a means of innovation. However, instead of focusing solely on business-related issues, data scientists will use their skills in a wider range of industries – such as academia and technology, as well as the typical business and finance industries a business analyst may work in.
What are the differences between data science and business analytics?
Business analytical roles tend to be more strategic, whilst data scientist roles are more technical. Business analytics is very specific to working in the business industry, whilst data science is much more broad and can be applied elsewhere. With a degree in data science, you’ll be able to work as a business analyst – but the opposite is not true. Let’s discuss the differences between the two subjects.
Using data and statistics
Both careers use data in different ways. Business analytics uses statistics found in business data to discover insights. This could be for a range of business industries, such as finance, marketing or retail. As a business analyst, your role will be predominantly based on statistical concepts which you will extract from both structured and unstructured data. Your findings will then be used to make informed decisions about the future of the business, as well as understanding the past performance of the company.
As a data scientist, your role will go beyond statistics as you work more on the front end. It’s a multidisciplinary field involving algorithms and data inference in a whole range of industries. After this is complete, you may then use statistics at the end of the analysis stage. As a data scientist, your role will be less strategic than a business analyst, and your work will not be used to make business decisions. You will focus more on mathematics and coding, using those skills to develop algorithms and finding connections between data.
Coding and work tools
As business analytics is more statistics orientated, your role should not involve much coding. However, there are a variety of other tools you may find yourself using commonly in your work, which include:
- Excel – for spreadsheets and calculation
- Tableau – for data visualisation
- SQL – for managing data and programming
- Python – a programming language
Data science, however, does involve much more coding and you will need a good knowledge of computer science to excel in this career. Some programming languages you may use in your role include:
- C, C++, or C#
Some tools you may use as a data scientist include:
- Keras – a Python interface
- PyTorch – a machine learning library
What can I do with a data science degree?
A degree in data science can lead to lots of exciting careers across a range of industries. Your degree will include aspects of mathematics and machine learning. You’ll have lots of opportunities to work in technology or even entrepreneurial roles – careers you’ll thrive in thanks to your strong technical background.
What can I do with a business analytics degree?
With a business analytics degree, you’ll probably already be interested in working in the business sector. You’ll need strong project management skills to succeed in this role, and will spend your time at university developing this alongside your analytical and business skills.
"This year is crucial"- Manh from Vietnam
Hear a bit more about what a degree in Business Analytics is like and why Mahn decided to study it in our video.
Data science or business analytics – which is best for you?
Ultimately, which subject you choose to study at university is down to your personal interests and career ambitions. If you love project management and analysing data to help make decisions, a more strategic role in business analytics might be for you.
Careers you could access with a business analytics degree include:
- Business Analyst
- Quantitative Analyst
- Operations Research
- Market Research
However, if you’re more passionate about technology and love programming and coding, you may enjoy a degree in data science more.
Here are some careers you may enjoy with the skills you gained on your degree:
- Data Scientist
- Machine Learning Engineer
- Applications Architect
- Data Architect
Start your business analytics or data science journey with Holland International Study Centre
No matter which of these degrees you choose to study, you can start your journey to studying business analytics or data science abroad at Holland International Study Centre. With us, you’ll receive a world-class education, taught in English, helping you to develop the skills you’ll need at university and in your career.
Study our International Foundation Year in Business, Economics and Social Sciences to build your academic knowledge and English language in skills to succeed as a business analyst or data scientist.