by Perry Lawton
As technical as it is, data analytics is a fundamentally human enterprise with profoundly human stakes.
When people outside the industry ask me about my work, I often tell them that I am in charge of the “beeps and boops” that guide pharmaceutical marketing campaigns. I transform the data that is generated by consumers’ and healthcare providers’ online activity into coherent stories that help pharma decision-makers stay on — or, if necessary, adjust — course.
This, of course, is a major simplification of what I do. As someone whose background is in data engineering, I have spent a significant portion of my professional life tinkering with the complex set theory and statistics that are embedded within programming languages like SQL to make sprawling unstructured datasets usable for other analytics team members and, by extension, clients.
For the first 18 months or so that I was at Saatchi & Saatchi Wellness, this was exactly what I did. I camped out on the back end, focusing almost exclusively on SQL database design, report population, and so forth. This ended up being a great way to find my feet in the pharma space — I had come to Saatchi from the utilities sector — but in the several years since, I have become progressively more involved with a variety of other aspects of Saatchi’s work.
This transition has been illuminating in countless ways, but perhaps the most compelling insight I have gleaned from being forced to think beyond the beeps and boops is that data analytics — even the most technical aspects of it — is a deeply human enterprise.
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