Big Data

Making the jump from being a data analyst to a data scientist – what skills do you need to learn and improve?

Data plays a huge role in modern business and is something that is extremely valuable to most global organizations. The data that is collected is, of course, only useful when it is interpreted, dissected and explored for future strategic planning. To this end, many companies now employ data analysts and data scientists to help. 

While both roles may sound the same, they are actually quite different. Data analysts tend to only look at what current data is saying, while data scientists also look at why and what it may mean for the future. Many people will start off as a data analyst but then decide to move on to the more senior data scientist role in time. 

Many people will achieve this by first getting the right education under their belt. A data science online degree from Kettering University is one course that certainly helps with this. By studying on this course at Kettering, you not only learn the skills needed to move up to data scientist, but also get to study at a truly world-class institution.

What are the key skills to transition from data analyst to data scientist?  

Brush up on problem solving and critical thinking

If you already work as a data analyst but want to move up to being a data scientist, then both of these soft skills are key. Whereas analyzing data might be focused on interpreting already presented data, this is not always so in data science. A data scientist will often need to think critically beforehand to decide on what data to collect and how to go about it. Problem solving naturally comes in when things do not go to plan and you have to find solutions. 

Coding needs to be on point 

Being able to collect large data sets, work out why something has happened, and then map how that may play out in future is achieved with computer algorithms. As a data scientist, you will often be responsible for deciding which algorithms to use and also creating your own. The net result is that data scientists need strong coding skills in programming languages such as Python and R.

Data visualization skills are a must

If you do not know about data visualization, then you need to find out more to work in data science. Data visualization is simply using the latest tech to represent data in a visual format. The visual nature of this approach is very useful for presentations and helping people to understand your findings. 

It is a big leap from data analysis to data science 

There is no doubt that data analysis is a key role in modern business and has its own merits. Data science is a step up from this though, and as a result, you may need to learn new skills to succeed. After this, it is just a case of updating your data science skills regularly to stay on point. 

Angela Scott-Briggs

Editor, | Interested in Innovations in Business, Finance, and Technology .

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Angela Scott-Briggs

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