Even as they try to figure out how much unstructured information they’ll need to sift through to solve future problems, IT leaders may want to start thinking about whether they or their staff can provide the expertise to make insights from analytics actionable, a research paper published by Ryerson University suggests.

The 30-page Closing Canada’s Big Data Talent Gap is based a national online survey and labour market study conducted through Canada’s Big Data Consortium, whose members include not only Ryerson but Deloitte, the CIO Association of Canada and ITAC, among others. While IT infrastructure and applications are increasingly being oriented towards deriving value from big data, the report’s numbers indicate there will be a dearth of people ready to understand it or apply it successfully:

We estimate Canada’s Big Data Talent Gap is between 10,500 and 19,000 professionals with deep data and analytical skills, such as those required for roles like Chief Data Officer, Data Scientist, and Data Solutions Architect. We further estimate the gap for professionals with solid data and analytical literacy to make better decisions at 150,000, such as those required for roles like the Business Manager and Business Analyst. 

Demand for big data-related jobs across Canada.
Demand for big data-related jobs across Canada.

 

Although the report mentions that some existing talent may lie within organizations’ existing workforce, including the IT department, there is scant mention of the role CIOs might play in big data projects. Instead, Closing Canada’s Big Data Talent Gap notes that there is increasing confusion around newer titles and roles that would be focused exclusively on analytics:

What is a Chief Data Officer, a Data Scientist, a Data Solution Architect, or a Business Manager? And what do they do? In the absence of common professional definitions and career pathways, organizations are struggling to clearly express their Big Data and Analytics talent needs, and prospective talent are finding it difficult to assess their suitability, interest, and candidacy in the field of Big Data and Analytics. Establishing common professional definitions and career pathways would improve labour market clarity; it is a foundational step to tackling Canada’s Big Data Talent Gap. 

What might be helpful here are more case studies in how CIOs are assisting with big data initiatives today. For example, I know several IT leaders who have started making use of tools like Hadoop and OpenStack, and in some cases their contribution will begin and end with implementing the technology and maintaining it as required. In other cases, though, it’s likely IT departments will be arming business units with tools that can visualize data or process it in some other way that doesn’t necessarily require a statistician or data expert. This is similar to what we saw in the growth and maturity of business intelligence tools, where ad-hoc queries to IT later morphed into more self-service applications.

Perhaps the most intriguing aspect of the report is the notion that big data will require an increased use of shared services models, or even the creation of centres of excellence devoted to analytics. While the latter is more typical of larger organizations, shared services in IT is already commonplace in a variety of industry sectors. Again, this is where CIOs could provide a lot of expertise and support as similar strategies take shape. It will probably take a while to close Canada’s big data talent gap. In the meantime, we may have to settle for a CIO-led stopgap.



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