Top of the data heap: First

Half of chief data officers surveyed by Exasol felt organizations' expectations of the CDO role were misinformed.

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So, who wants to make a career of amplifying the power of data? In an era when data is as valuable as gold, data professionals are in demand, and the career path now leads upward to chief data officer. 

However, CDO is a role loaded with plenty of uncertainties, as explained by Thomas Davenport and co-authors in Harvard Business Review, calling it "the most unstable C-suite job." As they explain, "Tenures are short, turnover is high, and as in the early days of the CIO role, many companies don't seem to know exactly what they want from its incumbents." The average tenure for CDOs is two and a half years, they estimate.

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In all fairness, it's different for within an environment like Ceridian than if I was a chief data officer of a bank. We're focused on overall data and intelligence governance for the entire organization. We're there to ensure from a customer data point of view [that] the application of artificial intelligence -- or as I prefer to call it, augmented intelligence -- is supporting the other product areas in terms of asking the right questions. 

I also look at how our advanced reporting is used, and how it goes to data visualizations, whether you look at predictive analytics tools or prediction and action. So data science, engineer, product management, [and] data related to customer data is what sits within my world.

Q: The way data is used and protected -- or not protected -- is an important issue these days, and must make the chief data officer's job very interesting.

Lloyd: We spend a lot of time working with our customers' data where we're allowed to by contract. This is not free-for-all-you-have-the-data, this is the customer entrusting us with their data, to de-identify it, and use it in ways that are ethical, and at the same time, beneficial. I think that combination of both technical and business skills is important here. 

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People may feel they have a mastery of something, but don't realize where their data is going, or how their data is being used. I think it's such an important thing for an organization to have that awareness, that understand how that data is actually being applied. 

The whole area of AI ethics, regulatorily as well as within organizations, is just developing. Look at the framework developed in New York, regulating the use of intelligence in hiring. It requires that you have to audit the way in which your algorithms are actually functioning. But there is no standard for audits. There are no general accepted accounting principles, like there is in finance, for looking at a financial system for AI technology. This is a great example of where the technology is running way ahead of the regulatory frameworks. 

That's always been the nature of technology.  We run ahead with it, and then we figure out how to lasso it, and get it into a place where people can feel comfortable with it, and even, although there are a lot of startups popping up, the startups' ability to support organizations in doing these kinds of audits for bias or drift and things like that within the intelligence side.

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