Terms come in and out of vogue on a regular basis. In recent years, the use of the term Machine Learning has surged. What I struggle with is that many traditional data mining and statistical functions are being folded underneath the machine learning umbrella. There is no harm in this except that I don’t think that the general community understands that, in many cases, traditional algorithms are just getting a new label with a lot of hype and buzz appeal.
At the recent IIA webinar on “Succeeding with Analytics: Overcoming Common Obstacles,” we had several excellent questions from participants in queue when we ran out of time. So myself and our two discussion leaders – Tom Johnston, SVP and Director of Client Analytics at Key Bank, and Marc LeMoine, Manager of Data Science and Modeling at Deere & Co. – addressed the questions afterwards. Here’s what we had to say.
It wasn’t too long ago that many people espoused the decline, if not death, of the SQL language and relational database technology in general. As a level set, remember that relational technology stores data into rows and columns and that the way to access relational data is through Structured Query Language (SQL).
I recently served as author – and ringleader – of an IIA research brief on obstacles encountered with analytics. We developed the brief in response to an inquiry from an IIA member that went something like this: “We’re ramping up our analytical capabilities and expanding use of analytics across the enterprise. What problems and pitfalls are we likely to encounter as we raise our maturity – and how can we overcome them?”
Analytics have gotten big and strategic in many organizations, to the point where analytical capabilities have the attention of senior management. Here are a few semi-random examples from the many analytical leaders and practitioners who attended IIA’s 2014 Winter Analytics Symposium earlier this month.
The business of healthcare is facing a defining moment. For the first time in decades, the growth in healthcare expenditures continues to be slower than the rate of inflation. In 2012 it was nearly one full percentage point lower at 3.7%. And job growth for the industry is nearly flat at 1.4%. How will the industry respond?
Just like the value of the Internet itself wasn’t really understood until it was in place, I suspect that we’ll all be surprised at how fast the Internet of Things becomes a part of our lives and how much we value it. However, there is an underbelly to the IOT that has the potential to severely disrupt how much of its potential is realized.
I had the privilege of leading a session at the Winter Symposium of the International Institute of Analytics, with a host of great companies discussing how they are embedding hardware into products and trying to drive improved supply chain performance in their products. In the sessions I attended, the topics ranged on a variety of areas, but focused on several important insights around risk, innovation and best practices for using the data at-hand.
While analytics can help healthcare organizations overcome their clinical and operational challenges, few have successfully applied the breakthrough tools and techniques now available. A short list of forward-thinking healthcare providers and payers are leveraging analytics to answer their most difficult questions. At IIA, we’re amassing more of these examples and case studies each day.