Access to information is a prime example. Data analysts don’t just focus on the 20% of the high-value, high-impact work; they are the only people doing the other 80% of analytics work that is routine and low-value, but also necessary. There’s a reason BI teams are often called report factories. All of this is about to change, fortunately. We’re starting to see the same technologies that have revolutionized the consumer space make their way into business.
What should Chief Data Officers be doing to effectively drive results? Surprisingly, the answer has little to do with the data itself. These days, no one can afford to ignore data. Of course, the chief data officer should try to maximise use of shared systems and resources, but their focus is to address the priorities of each line of business (LOB) while ensuring they’re broadly aligned with the business overall. Here are the main roles a chief data officer needs to fill, outside of the traditional security and infrastructure tasks, to help their organization succeed with data.
Machine learning can yield compelling insights within the scope of the information it has, but it lacks the wider context to know which results are truly useful. In addition, machines need people to tell them which datasets will be useful to analyze; if AI isn’t programmed to take a variable into account, it won’t see it. Business users must sometimes provide the context -- as well as plain common sense -- to know which data to look at, and which recommendations are useful.