I’ll be going to Florida next week to attend SQL Rally and present a session titled The Data Mining Lifecycle. I’ve spoken on data mining at least a half dozen times at different venues in the last year and I always get a good crowd. I’ve never taken a poll of the audience to find out why they decided to attend, but I think I have a good idea.
Why should you attend this session? You might be curious about data mining since you’ve seen it in SQL Server but you haven’t had a chance to dig into it. You’ve read about the future of in-database predictive analytics and want to know more. You learned about the mathematical part of data mining algorithms in college but haven’t had a real problem to apply them. Or you want to earn bonus points at your company by improving the ROI on a project you’re working on. These are all good reasons to attend, and it probably describes 99% of the people who have attended my sessions in the past.
At SQL Rally I’ll talk about how to get started with data mining by developing a problem statement and setting a target. These problems are all around us and yearning to be solved. As DBAs and developers we have data at out fingertips and we work on projects that provide us with great insight into the needs of the business. We hear data mining type questions constantly. How many times have you heard someone in your organization say “I wish I knew how the services we offer impact the customer experience” or “If I knew a customer’s annual income I would be more likely to market them the right products”. This is where predictive methods can provide a big bang for the buck. With SQL Server and the data mining algorithms you could predict a customer’s income, and you can forecast the customer experience based on the services your company provides them.
I’m currently working on a couple of projects from which I’ll use some real-life examples. One project is in the area of foster care and it’s a place where data mining can do so much good, both for the welfare of a child and in spending our tax money more effectively. When a child is placed into foster care, how much time will they stay in care until they are able to leave the system? When they leave foster care, how likely are they to return? What is the likelihood of a foster care placement being a successful placement, where the child is in a safe and stable situation? How likely is a child to be abused while in a particular foster care placement?
I’ll have examples like these and more, at least as many as I can cram into one hour. I hope you’ll attend and that you leave my session ready to make an impact with data mining at your organization.