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Big data skills gap remains a hurdle – IDC
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Big data skills gap remains a hurdle – IDC 

This was one of the issues that surfaced in the Big Data forum hosted by Canadian Government Executive at the Ryerson University on Tuesday.

“Big data can be used by government agencies to gather and make sense of information that can help them reach out to, service and engage more people,” said David Senf, program vice-president for infrastructure solutions at analyst firm IDC Canada, during his presentation titled Data Inflection Points in Canada.

Big data is a term used to describe huge amounts of data of data sets, often hundreds of terabytes or petabytes in scale. Big data is increasingly being used to describe not only structured data but unstructured data as well such as information that comes from sensors, social media, and mobile devices. Using the appropriate tools, big data can be analyzed to uncover insights that can be used to make decisions and make strategic plans.

Large corporations as well as Internet and social media companies such as Google which reshaped online advertising with the use of data and Uber which disrupted the taxi industry around the world with the use of data, typify the sort of organizations that make use of big data, according to Senf. However, in recent years, the public sector has shown increasing interest in big data.

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Canada Health Infoway, an independent, federally funded organization focused on accelerating the adoption of digital health solutions, held a hackathon to determine issues that should be dealt with concerning elder care and prescription medication.

“Using big data, participants in the hackathon discovered that there was overprescribing with some patients,” Senf said. “With these findings they were able to reach out to other organizations to find ways to remediate the situation.”

Big data has potential uses in the public sector in performance management, gathering operational intelligence, finance, business processes as well as analysis and discovery.

Typical big data projects tend to be completed in 14-month cycles. Usually organization spend eight months in data acquisition, four months in information processing and 3.1 months in business processing.

According to IDC the key challenges to big data adoption are:

  • Big data skills gap
  • Data acquisition issues
  • Issues around data such as data quality, data completeness, and data value

Even if IT leaders in government agencies determine what type of and how much unstructured data they would need to address their organizations’ current problems, finding the right personnel to with the right big data and analytics skills sets to make sense of the information will likely be their more serious problem.

The big data skills gap remains a top problem for public and private sector organizations, Senf explained.

“The challenges in big data and cloud are not in technology but in policy,” Phil McBride of Aimia Inc., a data-driven marketing, and loyalty analytics company. “For example, the technology for data sharing is there, but there should also be a common data sharing strategy.”

“It shouldn’t be the IT behind data but the analytics,” McBride said organizations, both public and private, should strive to develop the role of a CDO or chief data officer.

Very often, as companies rush to adopt big data solutions they turn to the chief information officer (CIO) to lead the strategy around the program. Typically, only very large corporations have a formal CDO. More often than not the CDO role is passed over to the CIO or added to the security function.

With this approach, he explained, organizations “are losing the value of the CDO.”

The CDO’s job is to link data to the corporate strategy, he said.

Patrice Dutil, a professor in the Department of Politics and Public Administration at Ryerson University, agrees.

“At some point the CDO has to happen in the public sector,” he said. “The CDO has to be the conduit between the data and government.”

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