As part of the course to prepare our organizations for Big Data, we all reach a place where we have to inject new blood into the group handling the problem. There is only so much training and retooling that can be done. Organizations need to introduce experienced people into play. While I will say that a Big Data technologist is easier to find than a Big Data analyst, it is a significant chore to find either.
On the technology side, the challenge exists in two parts: Big Data experience and experience in your marketing technology stack. In potential candidates, the unfortunate reality is that as Big Data experience increases experience in other “legacy” marketing technologies decreases. (I use the term legacy very loosely, because in the world of Big Data this could mean anything older than 18 to 24 months.) I also find that as Big Data ability increases so does their disinterest in (or disdain of, in some cases) “legacy” platforms. It helps if they don’t view your existing technology as some archaic tool that belongs in a museum’s Middle Ages torture exhibit next to a scold’s bridle or Scavenger’s daughter.
(This picture is from a discussion I was having at bar with a friend of mine. It attempts to illustrate the problem. Obviously, it makes more sense if you are in the right setting.)
The legacy experience is critically important to us in the marketing world. Big Data platforms will not be replacing our customer data warehouses in the near future. They will only complement the current technology stack.
On the flip side of the technology issue hides the Big Data analyst/engineer. These people need to be equal parts statistician and software engineer. Find me a significant source of model building, pig Latin coding, hive querying candidates that understand the legacy marketing world, and I will show you my unicorn farm. There are people out there, but they are in short supply. In reality, the issue is the maturity of the Big Data software suites. The software market has not created nor integrated their product sets into the Big Data platforms. It is occurring, and our Big Data analysts will go back to being statisticians. They won’t have to play the role of engineer. (As a side note, they have other roles in some organizations: report builder, data integrator, and random marketing idea validater. I won’t venture into these topics today, but make sure you are looking at all the things that prevent your analyst from generating real insights that have a meaningful impact on your business.)
I don’t have an answer for this hiring problem. The best solution I came up with was to sit at a bar and complain to a buddy of mine. The only thing I can say is that you have to be very mindful of the problem. There are many companies competing for these resources. This means that we have to do what we can to keep the ones we have and to have contingency plans in place when they take their next job offer. If you find an extra one hire them, because you will need them. On the brighter side, over time this gets better, and we are rapidly heading in that direction. UMF5YTJRDERG
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