We may not be deploying cloud servers at the drop of a hat, but the analytics community can take a few lessons from our friends in the DevOps movement. DevOps, short for Developer Operations, has grown around the art of scripting and automating the process of setting up your infrastructure (servers, databases, etc.).
I made an abrupt career change about ten years ago during the first dot-com recession, moving from a marketing role to working on credit card fraud detection projects. At the time I thought I was basically treading water – my old client was going away and I needed a job that would let me stay in Atlanta while my girlfriend and I got married. They needed an analytics guy and I needed a job.
Before I started working on the credit card fraud team, I imagined the fraudsters were unsophisticated criminals – high tech purse snatchers. What I discovered that summer surprised me.
Every day or so, I perform a little ritual on one of my projects that those of you who have blogs are well familiar with. I log into the admin console and moderate comments.
Which brings me face-to-face with THEM. Spammers, in overwhelming numbers. It has gotten to the point where I actually “grade” them on the quality of their blog comment spam. There is a definite hierarchy in terms of blog comment spam quality.
Spent most of the past week working on my first “serious” R scripting project.
I’ve been using R for a couple of years, generally as a free minitab replacement (using the R Commander GUI interface) and adjunct to Python projects. Most of my analytics projects to date have been coded in Python, since they are generally heavy on data (eg. require good integration with our data warehouse, dynamic SQL) and require either custom statistics or heavy text parsing. The latest project is somewhat the reverse – involving a relatively small dataset (very painful to assemble, since it reconciles data from two different transaction systems, but small) that I’m going to run a bunch of prepackaged statistical studies and graphics again. Sounds like a perfect fit for R.
In recent years, I’ve seen a new breed of analyst emerge. Indeed, more than a few of my superiors have encouraged me to join their ranks. This new breed of analyst knows statistics and finance but prefers to leave the coding to others. They have “people skills”. They know how to sit in meetings and provide “thought leadership” and “design policy”. However, these analysts cannot pull the actual data to support their point of view!
This approach to the technical side of our profession is doing them a serious disservice. Here’s why: