Page 89 - The EDIT | Q1 2017

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exponential rate, especially in our industry as every action becomes more measurable, trackable and reportable. However, the act of sifting through huge datasets and being able to determine what is relevant and what is not relevant to the business requires a unique blend of skills.
Let’s be clear — data reporting and data insights are not the same thing. Rarely do data insights lie bare and in open view. Converting data into data insights requires an individual to make inferences between data-points and to have the clarity of understanding to see the relationship between what might seem unconnected data-points in a report. The minimum pre-requisite for data storytelling relies on the individual possessing a base level of technical skill. Technical skills are required to extract and interrogate the data into additional layers (or secondary layers) of understanding to reveal the
David Jeffs OMG APAC
relationships and hidden insights contained within the dataset.
Typically, the necessary technical skillset requires
a modicum of statistical knowledge and excel proficiency. However, technical skills require an additional overlay of business acumen to be successful. The individual analyst needs to know what to look for, what is the context behind the analysis and ultimately what is the goal of the analysis i.e. what is the business issue we are trying to solve. The softer business acumen skillset is more important, and thus valuable to the team, then the harder technical skillset.
Put simply, selecting the relevant data-points is the basis of an insight. An insight can only truly be drawn from the data when the individual understands the connection between data-points
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