On IBM Websphere Decision Server

IBM recently announced "Websphere Decision Server".  This announcement states that this offering combines business event processing with business rules management system to accelerate decision making.


There are several ways in which event processing and business rules interact, some of them are: an event, derived by pattern detection, triggers a rule, which makes it event-driven decision; the other direction is also valid:  an execution of rules brings into decision and this decision can be reported as an event and may influence other decisions.  Triggering decisions is one of the major uses of event processing (of course it is not the only one,  e.g. event processing can be used for diagnosis or information dissemination), and it is a component in the automated decision making process, but these components mainly exist within islands (EP, business rules, optimization software and other means of decision support systems).    One of the areas we are working on (we had a short report on it within the "fast abstract" session of DEBS 2010, as we were not in a position yet to deliver a full paper) is a unified conceptual model of event processing and business rules, where both are generalized as decision agents.  this is still in the research phases, and not part of the product, nevertheless this announced offering provides step forward in achieving such an integration.   More synergies in the decision space are expected.     

Book review: The Decision Model

The last package from Amazon brought me the book entitled: "The Decision Model: A Business Logic Framework Linking Business and Technology" by Barbara von Halle and Larry Goldberg.

I have read a draft of the book before, at Barb's request, and wrote a review, from which one line was quoted on the back cover; I believe that the trend of modeling decisions and look at them in perspective of higher level abstractions will become more pervasive, and I view technologies like business rules, event processing and various analytics as building blocks in decision platforms that are going to be notable part of enterprise computing and managing much of the operational decisions. The book has three sections:

Section I puts the decision model in context, explains what is decision model, providing a background comparing decision models with data models, and positioning decision model in the SOA and BPM universe, it also explains the business value. This section is intended mostly for business users and managers that want to get an overview.

Section II explains the decision model in detail, discussing the structural, declarative and integrity principles, and comparing the decision model to the relational model, a motive repeating in previous books by Von Halle. There is even a chapter that is called "The decision model formally defined", but the formalization is in terms of explanations and tables, and not by formal writing, which I guess fits the target audience.

Section III is called "Commentaries" and is actually a collection of articles by the authors as well as by various people active in this space (John Zachman, James Taylor, Bruce Silver and more) discussing specific related issues such as: relations to enterprise decision management, standards, business decision maturity model.

Event based decisions and event processing are mentioned several times within the book, but are not thoroughly discussed. The focus is on facts and rules kind of terminology; a combined model that combines both rules and events is a natural extension, from the point of view of this decision model as well as from the point of view of event processing modeling. I have written before about decision agents, and since that time advanced on the thinking about such a decision agents framework. I'll revisit this issue in one of the following postings.

Bottom line -- the decision model book is a very good book to explain the book to various types of readers (the introduction maps the chapters of the book to the various types of users) and possible basis for both pragmatic foundations of rules technology, as well as a possible basis for a more formal basis for extended decision agents framework. More on this topic -- later.

More on Decison Management

Today is the last day of the 8 days holiday, and tomorrow - back to the office (well for one day only, since our weekend in Israel is Friday and Saturday, and Sunday is a regular working day), and I have a huge "to do" list that keeps accumulating, and a bunch of phone calls... Today, however, I have travelled with my family to Bet She'an, one of the biggest archaeological sites in Israel (around 70 KM from Haifa). The roman city was exposed and much of it has survived, as you can see in the picture above (there is much more).

Today - just a short posting as a follow up on James Taylor's posting, who is advocating for a while the notion of decision management. The following slide is copied from JT's posting and explains the difference between decision management and decision support




The difference, as shown, is between helping people to make manual decisions, which is the BI land, and make automated decisions, which is the DM land. One of the topics I am working on recently is the notion of "decision" as an abstraction which should be programmed directly by business users, and will hide a blend of technologies such as: BRMS, event processing and various kind of analytics; I believe that the next wave of computing will be centered around the ability to business users (or direct consumers) to program and the role of IT will be replaced by autonomic computing techniques -- we are not there, but this is something to expire. Event processing will play multiple roles in this setting, but I'll leave this discussion for another time -- it is late, and I want to advance in the book I am reading since tomorrow will be busy..

On BRMS and EP

This is a slide rule, an ancient means to do arithmetic calculations easily if one has some experience in working with it. When I took the matriculation exam in mathematics many years ago, the Israeli ministry of education did not allow the use of calculator, since calculator at that time was relatively expensive, and it was considered of giving unfair advantage to those who can afford it, however they allowed the use in slide rules, so it served me well at that time. Today slide rules together with logarithmic tables and typewriter found their way to museums, but other type of rules are still with us.

Some Blogs have recently made references to the recent Forrester report with the catchy name:
Must You Choose Between Business Rules And Complex Event Processing Platforms?

The Forrester reports discusses some confusion that exists between the two terms. It is true that there is some ambiguity of the word "rules" - on one hand rule-based is a kind of programming style that can be used to express event processing patterns, and between BRMS - a collection of products with a certain functionality. Forrester also claims that to add to the confusion there are people who use (or abuse) BRMS products to do CEP applications and CEP products to do business rules applications. You can read the rest of the original report for more details. In my previous posting about state processing and event processing I have talked about the difference between the two. In fact, BRMS products are processing the current snapshot (state), while event processing is about processing of the history of transitions, different kind of techniques and optimizations are used for each.
I have also blogged recently about decision agents, talking about the fact that event processing agents (at least some of them) can be a subset of a larger whole which can be called - decision agents. And indeed, while the two type of technologies are distinct, there is also a sense to look at them with a unified view. Here I share the vision of James Taylor who talks a lot about Enterprise Decision management which consists of business rules, event processing and analytics. We'll hear much more about this concept - more later.

On Decision Agents

Decisions are part of the enterprise life as well as the life of every individual. Take a decision that many of the readers have experienced: naming children. My wife and myself have realized in very early phase that we have completely different taste in names, so we have decided to agree on a protocol for how names are selected: taking turns - one of us is making a list of five names, and the other selects a name from this list. The selection is done only after the birth, and the list can be modified until the selection made. To be fair we need even number of children so each will play any of the roles equal amount of times (indeed we have four children which satisfies this requirement). This is actually work, none of us got the first priority, and none of us have to tolerate a name we really hate.

In the paragraph above I have described a manual decision, but increasingly decisions are made by computer software which makes or recommends decisions. James Taylor is constantly talking about "Decision Agents". I thought that it will be interested to look at this notion and discuss how it is related to event processing.

We can say that a "decision agent" has various properties that we can qualify as answer to questions:

• Why ? what is the reason that the decision agent activated. In the example above -- the birth of a child.
• which ? which information is needed in order to make this decision. In the example above --- the list of five names (which have been obtained by another decision or collection of decisions) .
• How? How the decision is made. In the example above --- by some human cognitive process, which may have reflection in a computerized decision agent.

Back to our world of event processing, we are using the term "event processing agent" to denote a software artifact that gets one or more event as an input, does something, and produces one or more events as an output.

The question is what is the relationship between decision agent and event processing agent ?


In a (not very recent) postings, Carole-An Matignon from Fair Isaac has attempted to demystify some terms. She used an analogy to the human body, saying that BRMS is the brain, while event processing is the sensor for the brain to get the decisions. So is event processing agent is a sensing agent ?

The answer is --- the terms decision agent and event processing agent do intersect, but none of them subsumes the other.

Returning to the decision agent questions.

The why question: A decision may be required since some situation has occurred, because some relevant fact has changed, or because somebody made an explicit request to activate the decision agent. In the first case (a situation has occurred), then this situation may be a simple event, but also may be a leaf of an event processing network. In this case, there may be some event processing agents that are part of the decision to activate the agent, so it is part of the brain.

The which question: Here again the information needed can vary -- it may relate to the present state, to the history of states, and transitions. Event processing agents can be used to prepare the required information, by taking events and filter, transform, enrich, aggregate, split and more. In this case the event processing agent is indeed a sensor, creating input for the decision.

The how question: There are various techniques to get a decision, detecting patterns on the event history may be a method to obtain a decision, together with other techniques, such as inferring from facts and rules, applying stochastic decision reasoning and more. This does not say that every event processing agent which performs "pattern detection" is indeed a decision agent, sometimes it just derive event that will be used directly or indirectly as input to a decision.
Interestingly, this is true for business rules as well. A business rule may derive new fact, the fact itself is not a decision, for example, it may be classification of a customer based on demographic information. The output of this rule is used as input to (another) decision agent. So BRMS like event processing can also play the role of both sensors and brain.

To summarize:

• An Event Processing Agent may be a Decision Agent, or provider of input or trigger to other decision agents.
• The same statement is also true for "state processing" business rule.
  
• A decision agent may be Event Processing Agent, but also can consist of several other types of agents.
• There may be blend of decision agents of various types inter-related. I'll write more in the future about this assertion.