I will be participating in the Analytics Executive Symposium being run on June 26th in Chicago by the International Institute for Analytics of which I am a faculty member.

The Analytics Executive Symposium is a unique and professional gathering of analytics champions who come together to hear and discuss the latest findings and research in analytics. The Symposium will feature the bi-annual meetings of IIA’s Analytics Research Councils (ARCs) for the Health Care and Retail industries. Special focuses on Analytics in the Enterprise will also be featured.
Please note: this is a by-invitation-only forum for IIA members.

Register here if you are an IIA member. To join contact the folks at IIA here.

I recently participated in an article in the Teradata magazine - A Beautiful, Cloudy Forecast – based on our research on predictive analytics in the cloud. As the article says:

The basic value proposition of predictive analytics in the cloud is clear: Organizations can make predictive analytics more scalable, more pervasive and easier to deploy. For many of the challenges organizations face in their journey to becoming analytic organizations, cloud-based solutions have much to offer.

Companies interested in this area can get all the details from this survey on our company site – decisionmanagementsolutions.com/predictive-analytics-in-the-cloud-survey-results. If you want any help getting started with predictive analytics in the cloud, drop us a line at info@decisionmanagementsolutions.com.

I am speaking at an event in Dresden, Germany on Decision Management (details here) on June 7 17:00 – 19:00 CET. I will be giving an introduction to Decision Management.

Business processes and business logic are two sides of same coin. Without an explicit consideration of business rules, process models can be incomplete and topics such as “compliance” is not considered.  In addition to the representation of business rules, we need above all a methodology to collect and manage the business logic.  This will be a relaxed discussion on the topic of “Decision Management”. I will cover why organizations need to understand and analyze decisions and point out the possibilities that come from the introduction of a systematic management approach to decisions.

The number of participants is limited so please register by e-mail to info@enterprise-design.eu - It is a first-come, first served event! 

There’s still time to register for the 2-day workshop in Europe next month. This covers the essentials of Decision Management, the effective use of business rules and Business Rules Management Systems and the role of analytics:

• Berlin – June 4/5 – Register here.

The class covers:

• An introduction to Decisions and Decision Management
• Categorizing and identifying decisions
• Characteristics and design of decisions
• Managing decision logic
• The role of decisions in systems
• Getting started and first steps

Hope to see you in Berlin.

I have been going to IBM IMPACT for a couple of years now. This year’s event is just around the corner – it starts on Sunday – and I am particularly excited about this one. While it’s not the first at which I have spoken, nor the first where there have been sessions on Decision Management, it does feel like the first where Decision Management will play a real role.

For instance, the Forbes Mini Main Tent will feature a Decision Management Solutions client talking about Decision Management as a strategic tool and he and I will then co-present on From business rules to decision-centric organization. On Tuesday I will be discussing Decision Management Trends with a great customer panel and then signing Decision Management Systems at the bookstore right after. Plus there are a ton of customer case studies and other sessions focused on Decision Management. In between I hope to hear some about IBM’s vision for Decision Management (among other things), catch up with the latest product demos and meet a bunch of folks working in the space. If you are planning to come, please drop by one of the sessions and say hi – I always like to meet blog readers.

Looking forward to IMPACT as I was, it was cool to be named an IBM Champion for Websphere.  I’d like to thank Jean Pommier and Ale Campioli  for nominating me – much appreciated! IBM says that they award the status to people who make a contribution to the broader community by blogging about their specialist subject (as I have been doing for years here at JTonEDM and previously elsewhere), by writing books (like Smart (Enough) Systems, the first book on Decision Management that Neil Raden and I wrote back in 2007 or Decision Management Systems, my new book), contributing thought leadership articles and white papers (see our library on decisionmanagementsolutions.com or check out the Decision Management Systems Platform Technologies report) and so on.

Being an IBM Champion is not a paid position but I certainly appreciate it as a nice way for IBM to recognize those who evangelize a topic and try to move the discussion forward.

The early bird pricing on our 2-day workshop in Europe expires this week. This workshop cover the essentials of Decision Management, the effective use of business rules and Business Rules Management Systems and the role of analytics:

• Berlin – June 4/5 – Register here.

The class covers:

• An introduction to Decisions and Decision Management
• Categorizing and identifying decisions
• Characteristics and design of decisions
• Managing decision logic
• The role of decisions in systems
• Getting started and first steps

Hope to see you in Berlin. Book now and get the early bird price!

It used to be that analytics were applied in batch, updating the database with a score or customer segment based on yesterday’s data.

It used to be that these models could take months to implement, so that the models themselves were based on data that might be months out of date.

It used to be that analytic teams could just produce scores or other predictive models and leave it to someone else to worry about how they might be used and integrated into operational systems.

But today’s world is real-time. Customers want answers in real-time. This means companies must decide in real-time using up to the minute data. And the world is changing fast so models need to be built with up to date data and rapidly deployed to keep them fresh and accurate.

Organizations need a decision management approach and a real-time infrastructure to take full advantage of predictive analytics:

1. Discover the operational decisions that make a difference to business objectives
2. Rapidly build analytic models that can influence these decisions
3. Wrap these analytics with the rules of their business – regulations, policies, best practices
4. Deploy these analytics quickly and accurately to their operational infrasturcture and hook them up to real-time data

Come to our webinar with Zementis on May 3 to learn more and see a live demo of their real-time infrastructure. Register here.

Skytree is singularly focused on advanced analytics, machine learning on massive datasets. They have been in development for several years and are based in Silicon Valley (with engineering teams there and in Atlanta) and the product was officially launched in 2012. They believe that machine learning will be at the core of solutions for big data (solutions like Google AdWords or Netflix recommendations are based around machine learning techniques) and their product is designed to make scalable, general purpose machine learning infrastructure readily available. Skytree is positioning itself at the intersection of large data scale (data warehousing, Hadoop, storage appliances, etc.) and advanced analytics (Statistical packages and predictive analytic workbenches). In particular their focus is on pattern recognition, predictive models and data mining and increasingly doing these things against streaming data in a distributed computing environment. Most customers are using Skytree Server with other modeling tools but some are new to machine learning and advanced analytics and are only using Skytree Server.

Skytree Server has been designed from the ground up to perform machine learning efficiently. The standalone software version is already available and is cloud and Virtual Machine ready with standards-based data import and export. Full scale out distributed support (thousands of cores) and support for real-time/streaming data is coming later this year and is currently in private beta. The server delivers high performance for classic machine learning techniques such as K-Means clustering, SVM Classification and Nearest Neighbor. Comparing to open source solutions like WEKA and R they report 3-200x improvements over the more efficient of the two in each case (they can show up to 10,000x relative to the slower of the two) on just one machine. When the distributed version of the product is released, comparisons with distributed open source solutions will be available as well.

The product is purely API based and takes a data file or stream from any standard data source (RDBMS, NoSQL, HDFS, flat files). Machine Learning algorithms are then applied (to both variable identification and modeling) and the engine either outputs a file containing predictions, in batch scoring, or creates a model file that can be used to score individual records interactively in production mode. For those who want to build and continuously refine data the streaming engine gets a high degree of accuracy quickly as data streams in. Multiple streams can feed a single modeling routine (important when modeling in the cloud as it allows lots of end points to stream data to a single modeling routine). The streaming engine uses a TCP connection so it can be connected, for instance, to a listener on a drip-fed data warehouse  to analyze a data stream as the data warehouse updates.

Skytree is one of the vendors listed in our Decision Management Systems Platform Technologies report.

I am giving a 2-day workshop on the essentials of Decision Management, the effective use of business rules and Business Rules Management Systems and the role of analytics in Europe this June:

• Berlin – June 4/5 – Register here.

Organizations must understand how to identify and classify decisions and how to assess the potential for business rules and analytics to support and improve those decisions. They need to understand the available technologies and approaches and the long and short term costs and benefits of these. This workshop introduces the principles of Decision Management and discusses its application to critical business processes as well as the appropriate use of available technology. We walk through how to identify and prioritize the decisions that drive your organization’s success, show how to analyze and design these decisions so they can be effectively managed, introduce business rules as a foundation to automate these decisions, link these decisions to data mining and predictive analytics and discuss how the role of these decisions in delivering smarter information systems.

Delivered as a 2 day workshop this class has several working sessions during which students will work in groups on problems that reinforce the key lessons of the class. These sessions will use both exercises and student’s own problems. The class covers:

• An introduction to Decisions and Decision Management
• Categorizing and identifying decisions
• Characteristics and design of decisions
• Managing decision logic
• The role of decisions in systems
• Getting started and first steps

This training is focused squarely on solving business problems and on how the various technologies should be used together. It is vendor-neutral and is for managers and analysts responsible for working with or interested in using business rules or analytics to improve their business and technology experts who wish to build systems and processes that make better decisions.

Hope to see you in Berlin.

A recent new twitter follower had an interesting post on his blog back in 2010 - The 4Ds “Detect, Derive, Decide and Do. I liked the description of this pattern and as it is a common one for Decision Management Systems I thought I would make a couple of quick comments:

• The Derive piece of this pattern might be driven entirely by the analysis of events as Jeff describes but it is also a potential place for Decision Management, especially when analytics can play a role. This step can involve determinations that could get quite complex and that could use predictive analytics or rules derived using data mining. Deriving patterns from data is something at which analytic models excel.
• The key role for Decision Management and Decision Management Systems, of course, is in the Decide step.  Not only are business rules management systems common here to manage the logic of a decision but the use of predictive analytics to inform and improve that decision is also a powerful use case. The key is to focus on this as  a decision and to model and manage it as such, rather than being immediately distracted by the rules or IF…THEN logic that drives it. I wrote about the differences between decisions, decision services and rules before.
• The overall pattern is one that is driving a number of Business Rules Management Systems to support event-handling rules. This allows the Derive and Decide steps to be managed together in a common environment.

Event-based systems are an increasingly common context for Decision Management Systems. If you want to know more about the technologies involved, why not download or read online our report on Decision Management Systems platform technologies.