- Adoption of analytics set to increase with push to become data-driven
- Despite various initiatives, shortage of skilled data and analytics personnel
IN the next five years, Singapore’s push to becoming a Smart Nation will propel the adoption of analytics as government agencies focus on investment in data, infrastructure and talent for data-driven insights, according to a recent International Data Corporation (IDC) research paper commissioned by SAS.
IDC’s State of Analytics Adoption in Singapore research examined the current analytics landscape as well as past and future growth opportunities for analytics in Singapore, SAS said in a statement.
“Analytics has always been integral in extracting indepth insights for business decisions and with Singapore’s Smart Nation vision, this role is only set to increase in importance,” said SAS Singapore managing director Francis Fong.
The analytics software market – for the four specific segments of advanced and predictive analytics; data integration and access; end-user query, reporting and analysis; and marketing – in Singapore is projected to grow at a compound annual growth rate of about 8.6% between 2016 and 2019.
This can be attributed largely to new growth opportunities, with self-service data discovery being the forerunner, SAS said.
With Singapore looking to establish itself as a global data and analytics hub, IDC found that despite the strong presence and growth of data centre parks, clear legal frameworks as well as government-led skills training initiatives, Singapore organisations are still finding it difficult to hire skilled data and analytics personnel.
While analytics has traditionally been adopted by key industries like banking, financial services and insurance (BFSI), and government, SAS is also observing an increasing uptake of visual analytics by vertical industries such as retail, transport and hospitality.
“Singapore’s push towards being a Smart Nation will introduce an exponential growth of data streams, resulting in more users demanding actionable insights from these data,” said Fong.
“In the wake of this technical skill set crunch, we’ve found that self-service analytics tools are democratising data to allow for data discovery and visualisation by non-technical users,” he added.
To further alleviate the shortage in analytics, SAS has forged strategic partnerships with major universities and polytechnics in Singapore, aimed at increasing skills, resources and competencies in business intelligence and business analytics.
The research also put forth how the Smart Nation journey will see increasing investments from government agencies as they focus on becoming data-driven.
This in turn will provide opportunities for organisations to leverage on the following:
- Infrastructure: The continued enhancement of network and communications infrastructure will see the building of extensive sensor networks to collect more data. A ‘Data Centre Corridor’ is also expected to be formed to allow companies quicker and easier access to domestic and international markets;
- Data: The creation of a trusted data marketplace where private and public data sets are systematically available. A data-as-a-service pilot initiated by the Infocomm Development Authority of Singapore (IDA) is aimed at encouraging standard data sharing from private organisations; and
- Talent: Educational institutions are working on building labs and courses to groom data and analytics talent; the government is also working with industry players to establish a Company-Led Training (CLT) programme.
“The Smart Nation initiative bodes well for organisations operating in Singapore as they strive to compete and innovate in the complex global and regional economy,” said Chwee Kan Chua, associate vice president of the Big Data and Analytics & Cognitive Computing Practice at IDC Asia/ Pacific.
“The success of Smart Nation will be dependent on organisations being able to readily access actionable and automated insights from the massive data curated.
“Such insights will be delivered by analytics with cognitive features such as machine and deep learning capabilities,” he added.
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