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James Taylor

I will use this blog to discuss business challenges and how technologies like analytics, optimization and business rules can meet those challenges.

About the author >

James is the CEO of Decision Management Solutions and works with clients to automate and improve the decisions underpinning their business. James is the leading expert in decision management and a passionate advocate of decisioning technologies business rules, predictive analytics and data mining. James helps companies develop smarter and more agile processes and systems and has more than 20 years of experience developing software and solutions for clients. He has led decision management efforts for leading companies in insurance, banking, health management and telecommunications. James is a regular keynote speaker and trainer and he wrote Smart (Enough) Systems (Prentice Hall, 2007) with Neil Raden. James is a faculty member of the International Institute for Analytics.

February 2010 Archives

My co-author on Smart (Enough) Systems, Neil Raden, has written a great white paper on in-database analytics that is available from Sybase - Analytics from the start. This paper introduces the key concepts, discusses some of the key issues (our book contains more tips in this area) and describes some strong case examples. Well worth a read. As Neil says:

Advanced analytics will be adopted by most organizations and attain the status of "must have." While the majority of people in organizations will not become quantitative experts and modelers, the affect of predictive models will be felt across the organization and beyond. They already are. It would be wise to take steps now, and a good first step is to begin evaluating technology solutions that will be suitable for the development and implementation of analytics. From a technology perspective, one clear requirement is an analytic engine embedded in your analytical database technology.
The approach Neil describes is one we see more and more as in-database and in-warehouse analytics become more common. This particular paper talks about the Fuzzy Logix libraries embedded in Sybase IQ but . Fuzzy Logix is one of the sponsors (with SAS, Oracle, Adaptive and Aha!) of the operational analytics research I am doing for BeyeNetwork. Look for it on the BeyeResearch site in a couple of months and, meanwhile, participate by taking the survey.

Posted February 23, 2010 8:05 AM
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I got a briefing from Quantivo recently. This is a company focused on behavioral analytics - uncovering patterns within the mountains of customer data that companies have - web analytics and point of sale data for instance. They help companies find these patterns, find the insight that they are not seeing with their current tools, and then help them make better decisions. Quantivo started with Retail (market basket analysis and promotion analysis) then expanded beyond that, including web analytics, and acquired new customers throughout 2009. The focus now is on their latest product release, Quantivo 4, and a strategic partnership with Webtrends (who now resell Quantivo). Quantivo has signed some good retail, B2B, marketing and insurance customers, including OSH and Cisco WebEx. Quantivo describe themselves as offering advanced analytics at scale in the cloud.

Quantivo sees companies trying to find who did what, when and why so they can target customers and promote more effectively. Companies want access to their data and effective answers without having to go through the IT department. The need is to democratize access to data and the answers hidden in data. People have a thirst for answers that is not being met by the BI infrastructure IT departments have implemented. In particular there is a gap between analytics and action - data is too far from decision makers who anyway can't use the analytic tools that are available. Quantivo has tried to re-think the current data/ETL/Data Warehouse/BI/Data mining tool stack and do this re-thinking in the cloud to take advantage of the flexibility and elastic computing power available that way.

Their target user is a business analyst who wants to know things like who purchased movies and games together or what coupon users bought the 10 days following their use of the coupon, which campaign drove high-value repeat customers etc. A marketing analyst, for instance, trying to figure out what works and what does not. These are "advanced" analytics not because the questions are conceptually difficult to ask or because the representation of the answer is complex but because they are hard to answer using classic OLAP/reporting tools.

Quantivo 4 has focused in a few key areas:

  • Dynamic Behavioral Segmentation Context filtering and context-specific queries (over a web session, lifetime of a customer, product range etc), multi-attribute segmentation and segmentation comparison
  • Drag and drop web UI to make the solution accessible to business analysts
  • Instant export so can load into some tool to take action using downstream applications

The web environment allows business analysts to create and manage worksheets (which can be shared between users). These worksheets can be built using drag and drop feature from lists of dimensions and measures in an OLAP-like way. Performance is good, with large numbers of records being processed quickly and filters can be easily added to restrict the data and see results. Within the results users can start to select elements (one department, say) and make them a comparison target. This allows them to see, for instance, what else people who bought from a specific department purchased at the same time. Or what people bought in the week following a purchase from that department.

Users can drill down, navigate around etc in an easy to use and pretty responsive interface. This is the kind of analysis most people would do in data mining or high-end analytic tools but made available in a very easy to use end-user analyst interface. These worksheets are live and updated when new data is uploaded and they can be shared across users. Customers' data is uploaded to Quantivo, which is hosted on Amazon EC2.

At any point the user can take the population (of people who might be a good target for instance for an offer) and export to a marketing application etc. Quantivo makes it easy to access the result of a worksheet programmatically and they are working on more advanced APIs also.


Posted February 10, 2010 5:23 PM
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Predictive Analytics World, February 16-17, 2010 at the Palace Hotel in San Francisco is turning into the biggest yet. I am going to be speaking on analytic journeys and giving a workshop on putting predictive analytics to work and there are some great keynotes from Andreas Weigen (ex-amazon.com), Kim Larsen (Charles Schwab) and conference chair Eric Siegel. As usual there are lots of great presentations (besides mine) and I highly recommend it. You can get use the code SPEAKPAW010 to get a 15% discount off a two-day pass and find more details at predictiveanalyticsworld.com. If you come, come by and say hi after my presentation or while I am introducing people in Track 2 on the first day.

And if you are interested in analytics, don't forget the study I am doing with B-Eye Network on business analytics - it will discuss the motivation for adopting business analytics and how you should approach the evaluation of business analytics as well as how business analytics fit within an enterprise and business architecture, risks and issues, benefits and challenges and more. You can help by taking the survey - http://www.zoomerang.com/Survey/?p=WEB22A3HRGXRBS.


Posted February 2, 2010 8:52 PM
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