Written on 20th September 2021 - 3 minutes

Data science vs business analysis – what’s the difference?

Data science vs business analysis

Data has become a fairly ubiquitous word these days. We all know its value, we all know we should be doing something with it but knowing exactly what to do with it can seem like the hardest question to answer. Our data may be disorganised, disparate or outdated, and sitting on top can often be a reporting tool that feels like you need a PhD to use. When dealing with data in any organisation, it’s normally difficult to see the woods from the trees, therefore as is often the case it’s time to bring in the experts to help. So, if there is some scary data in your neighbourhood, who you gonna call? (Hint: it’s not the Ghostbuster’s), it’s more likely to be a Data Scientist and a Business Analyst (BA) – and while it may seem like Data Scientists and BA’s wouldn’t have much in common, when we’re talking about data there might be more similarities than initially meets the eye.

The International Institute of Business Analysis describes the BA as an agent of change. Their key responsibilities are to analyse systems and processes within organisations and define solutions that deliver the most value to stakeholders. When we talk about data, the BA’s role is often to build and evaluate reports and provide recommendations to a business based on their findings. In this way, the BA is concerned with finding trends, measuring performance, or simply identifying bottlenecks in processes through an organisations data and then offering possible solutions to decision-makers. Data is used in this context to help the BA identify areas in the business that may require process change, allowing them to provide evidence-based research to stakeholders on the course of action that will most benefit the organisation.

When we talk about what a Data Scientist does, it’s important to highlight a single word to help us understand their jobs – scientist. Just like regular scientists, Data Scientists are concerned with developing hypotheses and then seeking to prove them. However, unlike a traditional scientist, this isn’t done with chemicals in a lab, it’s done with large quantities of data. Usually, this raw data has to be organised, formatted and massaged by the Data Scientist, after which they can write complex algorithms, including machine learning and artificial intelligence conventions to model customer behaviour, predict future trends and code more efficient systems. Unlike the BA, the Data Scientist actually wades into the data and wrangles it into a form whereby it can be used to benefit the organisation, whereby a BA is more concerned with interpreting data that already exists.

It’s important to note that both the BA and Data Science disciplines have a lot of overlap for a single reason – the goal is to improve the performance of the business using data. However, it’s how they accomplish this that sets them apart. The BA will often work with the data to propose changes in business processes to stakeholders, compared to the Data Scientist who will work with the data to forecast and model trends as well as create code to make processes and systems more efficient. So next time you call the data experts at Software Solved, remember to ask for both a Business Analyst and a Data Scientist to cover all your databases! (Pun intended).

If you’d like to find out more about how we can help you with your data, please get in touch.

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