In my previous post, I had talked about “Debunking Myths about Watson” and now I am going to talk about Predictive Analytics World. So is there a connection? Well, one connection is Dr. David Ferruci who is an IBM Fellow and the principal investigator for the Watson/Jeopardy is one of the keynote speaker at Predictive Analytics conference. He also led the team who developed UIMA. Also, the other connection is that I had the opportunity to know Eric Siegal for some time, who is an expert in predictive analytics, founding chair of the Predictive Analytics World and is also a former computer science professor at Columbia University. Eric is very knowledgeable, practical and articulate about this area and really knows how to simplify this topic. The last reason is that line is blurring between so many of these technologies and we will continue to see overlap — the effect will be that we will also see more and more reorganization in future enterprises. There is a always a difference between how vendors build categories for different technologies and how businesses view them.
Predictive Analytics by definition is a business intelligence technology that produces a predictive score for each customer or a prospect. Some people in the industry consider analytics as a different discipline than business intelligence — because conventionally BI is more about what happened in the past or what is happening now but analytics is why it happened and what will happen in future. Predictive analytics (one of the key areas of analytics among areas like data mining, forecasting, optimization, text analytics etc.) is becoming increasingly important as marketing is the main business driver behind this discipline. It was already being used for many years in the applications for fraud detection, credit scoring and insurance pricing. But now there is almost an explosion of this discipline in the areas of direct marketing, customer retention, product recommendations, behavior-based advertising, email targeting and leads scoring. The academic term for predictive analytics is “machine learning”. As Mark Twain said, “The art of prophesy is very difficult, especially with respect to future” but the good news is that predictive analytics doesn’t need to be very accurate to provide value. It can help you answer questions like “People who buy life insurance are probably more likely to buy a luxury sedan.” Probably, we know this already but it matters when you are dealing with large volumes of data about customers and their interactions with products and services. Also, if you know in advance, which of your customers are likely to leave you, you can take measures to hit only those customers with right campaigns to retain them. Business Intelligence doesn’t get more actionable than that! Forrester research expects the growth to double within five years as ROI is very high.
You might consider going to Predictive Analytics World, October 16-21 in New York City (pawcon.com/nyc) which will give you deep dive in the Predictive Analytics. There is also a new conference Text Analytics World (tawgo.com/nyc), co-located with PAW NYC. You can get a 15% discount on the 2 Day Conference Pass by using this code: PMNY11
Review Title
There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don't look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn't anything embarrassing hidden in the middle of text.
8.1
If you use this site regularly and would like to help keep the site on the Internet, please consider donating a small sum to help pay for the hosting and bandwidth bill. There is no minimum donation, any sum is appreciated - click here to donate using PayPal. Thank you for your support.
Pros
- Pors Item One
- Pors Item Two
- Pors Item Three
- Pors Item Four
- Pors Item Five
Cons
- Cons Item One
- Cons Item Two
- Cons Item Three
- Cons Item Four
- Cons Item Five
