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Processing power, analytics enabling machine learning across industries

18th August 2017

By: Schalk Burger

Creamer Media Senior Deputy Editor

     

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Analysts, businesses and whole industries have become empowered by the flood of data that can be processed to build stronger models and make data-driven decisions in shorter periods, says credit bureau Compuscansenior data analyst Jacobus Eksteen.

The powerful combination of machine learning and human learning in the rapidly changing world of analytics will result in significant opportunities and efficiencies in various industries, he avers.

Analytics has become a powerful tool used by companies to identify and understand what to do, when to do it and how to do it to enhance efficiency. Greater availability of highly sophisticated software packages and algorithms, an increase in processing power and a decrease in processing cost have driven adoption and use.

“With more data, storage and analysis, coupled with cloud computing, the realm of data analysis has expanded and machine learning is now equipping a variety of industries in which great amounts of data are generated to make quicker and better decisions.”

Machine learning is an evolutionary by-product of artificial intelligence and computer science that enables computers to ‘learn’ without being explicitly programmed to perform certain tasks, he explains.

“Machine learning automates repetitive tasks and enables employees to perform more complex and fewer dull tasks. While some current job roles will not exist in ten years’ time, there are also jobs now that didn’t exist ten years ago. In fact, technologies, such as machine learning, have opened up new doors for employment opportunities and have drastically changed the way business is done.”

Machine learning can be used to enhance disease assessment, diagnostics and treatment plans by allowing for the monitoring and prediction of epidemic outbreaks based on, for example, satellite data, Web information and social media updates.

The aerospace industry is investigating the application of machine learning in the form of data-driven adaptive training to optimise the time taken for each trainee to become a proficient pilot. This will help to address the need to increase the global training capacity of pilots without jeopardising flight safety.

Machine learning is merely a tool – one of many that need to be understood and used properly, but a focus on developing skill sets may be necessary in the near future to avoid the risk of redundancy in the workplace, he advises.

Edited by Martin Zhuwakinyu
Creamer Media Senior Deputy Editor

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