The use of data analytics and machine learning might still be at nascent stages in Malaysia, but the benefits could be immense once the technologies are commercialised.
Dr Vala Ali Rohani, the data scientist lead at the Asean Data Analytics eXchange (ADAX), said that the centre, which was established by the Malaysia Digital Economy Corporation (MDEC) would help boost the adoption of data analytics and place Malaysia as a hub in Asean.
One particular project that Vala has been managing is the National Consumer Confidence Predictor (NACOP), a project done by Berkshire Media Sdn Bhd in collaboration with University of Malaya.
The research project aims to create an alternative approach to the traditional questionnaire survey-based framework of measuring consumer confidence.
According to Vala, a team of eight academicians and 25 data professionals collected about 1.2 million pieces of data from social media, which were then cleaned before being analysed by different machine learning algorithms.
He said that the research findings could provide accurate insights into understanding purchasing behaviour and speed up the release of official Consumer Confidence Index figures.
The project is on track for commercialisation in 2018 and has the ability to generate reports on a daily and quarterly basis, unlike traditional reports that are time consuming to prepare.
Another potential use of data analytics technology is the upcoming Brain City Project, which could be used to improve traffic management in the Klang Valley.
For instance, Vala said that the insights could be use to manage and sync all the traffic lights to smoothen traffic flow and reduce the congestion.
However, the project is still at the early stages of discussion.
Despite all the immense potential that data technologies could bring, Vala also believes that Malaysia still has a long way to go.
“The main challenge that I see in Malaysia is that 90% of the projects here are limited to descriptive analytics.”
Descriptive analytics is the earliest stage of data processing that involves the use of historical data to provide useful insights and prepare the data for further advanced level of analytics.
Another challenge in Malaysia is that companies are just starting to collect data and have yet to start with the analytics process.
“The best way for organisations to approach data analytics is to first find the business problems and pain points. Then only could we have a good idea on what could be improved. Otherwise, it would be just blind decisions based on graphs generated from the data analytics process.”
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