Africa needs data scientists: What will it take to train them? | IDG Connect

Vincent Matinde, international IT Journalist summarizes, "What makes a good data science and how can African countries fill the shortage?"  

Photo: IDG Connect

The lack of skilled labour in the data science and software engineering sectors is a problem worldwide but it is especially true in Africa.

According to Dramane Traore, the Founder of Data Fintech, a Nairobi based data broker, the need for data scientists will shift when businesses realise the value in evaluating their own data and using public domain data.

“Employers, (private and public) and especially top management within those organisations are behind the curve when it comes to use data to make strategic decision. As a result, the market is not creating the conditions for more data analysts,” says Traore.

Government bodies and organisations everywhere are digitising their business and this is producing huge amounts of data but Africa has not been progressive when it comes to mining.

Photo: Wanjugu Irene

“The amount of data will keep on increasing even more rapidly,” Irene Wanjugu a technical mentor at Moringa School, a Nairobi-based coding school, tells IDG Connect.

“We have seen that how well this data is ‘handled’ determines the survival or fall of economies and companies. This is also the case for African economies. The field of data analysis is therefore of paramount importance to the advancement of these economies and systems in Africa.”

What makes a good data scientist?  
Wanjugu classifies the qualities needed to get into the data science field as two-fold. One, is getting a grip of the tools for data analysis. She terms this as the hard skills. The plethora of tools that are out there can be overwhelming but they are becoming accessible due to the expanding nature of internet connectivity.

The other set of skills are the soft skills, Wanjugu said. These are the non-technical ones but can lead to improved delivery of analysis.

“A data analyst needs to want to dig deeper into the data. Not just accept the initial results provided by the data but to ask why the results are as they are. Digging deeper is a mind-set,” says Wanjugu. “They need to think outside the box – both in the methods they use for analysis and also when displaying and reporting the findings of the analysis. They should be able to adjust the findings on the fly, regardless of pre-conceived notions about the data.”...

How can African institutions train good data scientists?  
“The term ‘Data Scientist’ is essentially a fancy word for an experienced statistician; that is, a statistician with a modern twist,” Wanjugu explains.

She adds that institutions in Africa have been teaching statistics and mathematics for a very long time and it is about time they combined this with the tools that are out there in the market place.

The language R and statistics have been the traditional skill set data scientists need to have. Most of these skills have been taught in the confines of a traditional education setting. However this is changing. Many programmers are accessing their skills online and with improved connectivity, African students are not left behind.
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Source: IDG Connect