Business analytics comes in three (3) general flavors: descriptive, predictive and prescriptive. See: …Continue
Added by Michael Walker on August 27, 2013 at 2:00pm — No Comments
There’s been a great deal of discussion over the past several weeks regarding data mining and predictive models. Terms like “meta data” and “algorithm” are fast moving from the domain of IT practitioners and into the realm of water cooler discussion. This might be a good opportunity to briefly review some of these concepts in order to better understand data mining practices and standards.
First, some terms.
Meta Data - refers…Continue
Added by James Sullivan on August 15, 2013 at 6:00am — No Comments
Added by Michael Walker on June 19, 2013 at 9:39am — No Comments
Predictive analytics is now sexy in the business world. While predictive analytics has many benefits and can help organizations gain competitive advantage, the hype may be causing false expectations. There is a mistaken…Continue
Talk on PMML and Predictive Analytics to the ACM Data Mining Bay Area/SF group at the LinkedIn auditorium in Sunnyvale, CA.
Data mining scientists work hard to analyze historical data and to build the best predictive solutions out of it. IT engineers, on the other hand, are usually responsible for bringing these solutions to life, by recoding them into a format suitable for operational deployment. Given that data mining scientists and engineers…
Added by Alex Guazzelli on October 2, 2012 at 8:12am — No Comments
The goal of Data Analytics (big and small) is to get actionable insights resulting in smarter decisions and better business outcomes. How you architect business technologies and design data analytics processes to get valuable, actionable insights varies.
It is critical to design and build a data warehouse / business intelligence…
Added by Michael Walker on September 19, 2012 at 11:57am — No Comments
There is no question that the USA (in fact, most of the world) would be well-served with more quantitatively capable people to work in business and government. However, the current hysteria over the shortage of data scientists is overblown. To illustrate why, I am going to use an example from air travel.
On a recent trip from Santa Fe, NM to Phoenix, AZ, I tracked the various times:
Added by Neil Raden on June 27, 2012 at 10:00am — No Comments
Added by Patricia Tenanty on April 13, 2012 at 7:30am — No Comments