get you a data engineer
Hey there CEO person. I get it. You recently read an article. You recently read a blog post. A conference where the main topics had titles like “AI in…” got you intrigued.
Whatever it was, the prospect of using mahcine learning and AI to solve business problems has got you intrigued. Machine Learning offers many benefits. My raison d’être for this blog post is to convince you that 1.) your instincts were right, ML has tangible benefits and 2.) one of the larger benefits is actually an update of your systems. Let’s work backwards on those.
ML as a Harbinger
Most businesses, earnestly will answer the question “do you make data driven decisions” or even more broadly “do you have data” with a resounding yes. This is well and good until someone explains what “data” means in a new context. In the past, a “data driven decision” meant something on a spectrum of “we have a dashboard that tells us an aggregated statistic that we use downstream for decisions” to “we have someone who statistically measures significance between distributions of our sales.” This is an outdated view of “data drive decision making” though. Things have improved. If you haven’t had a data scientist on staff, these changes might have happened without your knowing. Machine learning is nothing new. Two widely used models: XGBoost and CART have been around since the 80s. Many other model are even older. Modeling techniques have roots in models from the 1800s, so what is the big differentiator? Data. These models were created when “data” respresented some measurements that a farmer took at the end of crop growing season. We have since progressed e14xponentially. The ability to store and transform data is the game changer here. Since the early 2000s with Google’s paper on horizontal scaling of data stores (which would later become Hadoop) we have seen massive improvements over the datastores of old.
If there was ever a time to migrate your legacy ERP system into the cloud, if at least the database, it is now.