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Data cannot work in isolation of analytics

The proliferation of connected devices has resulted in the exponential increase of real-time data, but data on its own means very little if proper analytics does not take place. Frank Rizzo, Data and Analytics Leader of KPMG South Africa, discusses the importance of data and analytics.

"The four big technology trends (cloud computing, big data, mobility, and social networking) are all adding fuel to the fire. And while there is a lot of hype around the sheer volume of data available, the question is: What does it mean from a business point of view?"

Rizzo believes that the practical elements around the decision-making process often revolve around whether the decision maker has the right data to make the right decisions. But what often happens is that he is focusing on the amount of data and not whether the information he has is enough to infer decisions on.

"The three Vs of data examine its volume, variety, and velocity. At KPMG, we also talk about two additional Vs; the veracity (or integrity) of data, and the value that it provides the business. All these elements need to be used in conjunction to help decision makers respond to a specific business problem they need to solve."

The quality of data used

Another important element to be cognisant of is the quality of data used. Rizzo says that in the past several months there has been a marked increase in public and private sector organisations putting tenders out for specialists in data quality.

"It seems that we are all trying to solve the world's problems with data and not many are checking the quality of the sources. Adding to this challenge is the amount of real-time data being generated. So the variety and volume of data have increased massively."

Companies are starting to realise the necessity of analytics, but quality data needs to be there first. A lot of experimentation is still happening in the South African marketplace around the real-time analysis of data but, according to Rizzo, there have been no massive successes as yet.

"It is clear that there is a gap in the market to draw out insights from the tools that companies are using. This could very well boil down to a resources issue. The reality is that you need people who understand mathematics, science, statistics, technology and business. Local universities have started offering modules on data science but we are not quite there yet."

He says that these data scientists are often referred to as 'unicorns' in the field because they do not exist. However, just as business and technology have merged in recent years, so too will the science of data combine into the workplace.

"There will be significant demand for skilled people in these areas. Data proliferation will increase exponentially and so you need the specialists who are able to filter it and extract value from it," concluded Rizzo.

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