Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Decisions in IBM WebSphere/ILOG BRMS
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Business Rules > Decisions in IBM WebSphere/ILOG BRMS
Business RulesDecision Management

Decisions in IBM WebSphere/ILOG BRMS

JamesTaylor
JamesTaylor
4 Min Read
SHARE

Christian de Sainte Marie from the ILOG group at IBM presented to the OMG Decision Model Notation day on the role of decisions in the ILOG Business Rules Management System. Christian started by describing a BRMS (see my brief on what is a BRMS) and the ILOG BRMS in particular.

Christian de Sainte Marie from the ILOG group at IBM presented to the OMG Decision Model Notation day on the role of decisions in the ILOG Business Rules Management System. Christian started by describing a BRMS (see my brief on what is a BRMS) and the ILOG BRMS in particular. He drilled down a little into rulesets – stand-alone executable containers for a set of rules that can represent a decision and be deployed as a decision service or can be part of a decision (see this post on decisions, rulesets and rules and how they relate). Obviously these rules must act against business objects – fact types – and like most BRMS the IBM environment takes technical object models (database designs, XML structures, Java objects) and presents them as a business friendly object/fact model by layering a vocabulary on top. Christian also made the point that the use of an underlying conceptual model that can be shared is critical for modeling and sharing.

The ILOG BRMS supports a number of metaphors to describe rulesets – decision tables and decision trees for example. Their use of decision tables is just as Jan described in this presentation and decision trees are used where segmentation or sharing of common conditions are important. At the end of the day, both metaphors execute as a set of business rules – a ruleset. Essentially the metaphors describe the structure of the rules and the data in the decision table, for instance, is combined with this structure to create a set of executable rules. With IBM’s acquisition of SPSS the integration of predictive analytics with business rules has moved on with models being imported as decision trees using PMML. Finally of course many decisions require multiple rulesets and so ILOG like other BRMS supports the notion of a ruleflow – perhaps better described as a decision flow. These looks like simple processes but are limited to basic flow concepts (a small subset of BPMN for instance). A step might be a simple ruleset but it might also be multiple packages of business rules with pre-conditions etc.

In general the use of a BRMS is different from decision modeling – it tends to be bottom up (assembling rulesets into a decision for deployment as a decision service) and much more technical (specifying execution styles etc). It is also true that there are non-declarative elements of business decisions.

More Read

SAP and The Hoover Dam
Celebrate Corporate Compliance and Ethics Week!
4 Ways to Use Business Intelligence in Your Business
Data Management: Reaching Into the Cloud
First Look: FICO Decision Optimizer

Christian wrapped up by saying that business rule application design and decision modeling are complementary but not the same – that they are orthogonal to some degree. To be interoperable, to work well together, they need to share vocabulary and the “process” of decision making must be manageable as well as the rules.

Previous in series
Copyright © 2011 http://jtonedm.com James Taylor

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Market Trends
AnalyticsBig DataBusiness IntelligenceBusiness RulesData QualityPredictive AnalyticsWeb Analytics

In a World Full of Data, Can Analytics See the Market Trends?

4 Min Read
decision management
AnalyticsBest PracticesBig DataBusiness IntelligenceData ManagementData MiningDecision ManagementModelingPredictive Analytics

The Role of Decision Requirements in the Analytical Life Cycle

4 Min Read
Image
Cloud ComputingData MiningData VisualizationDecision ManagementHadoopMarket ResearchPolicy and GovernanceRisk Management

Where in the World Does All this ESRI World Data Come from?

11 Min Read

Collaboration Is Vital to Success [VIDEO]

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?