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
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 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

cybersecurity tips for data centric businesses
5 Essential Cybersecurity Tips For Data Centric Businesses In 2021
Want More Actionable Information from Your BI? Support Your IT Team’s Need for Data Warehouse Automation
BI on Tablets Brings Right Info to Right People at Right Time
Is VoIP Offering You Any Real Benefit?
Clinical Trails Optimization – Business Analytics to the rescue

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

warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive
stock investing and data analytics
How Data Analytics Supports Smarter Stock Trading Strategies
Analytics Exclusive
qr codes for data-driven marketing
Role of QR Codes in Data-Driven Marketing
Big Data Exclusive
microsoft 365 data migration
Why Data-Driven Businesses Consider Microsoft 365 Migration
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsBig DataBusiness IntelligenceDecision ManagementITModelingPredictive AnalyticsSoftwareUnstructured DataWorkforce AnalyticsWorkforce Data

Big Data and Analytics In Sports: A Game Changer

7 Min Read

More Business Rules Consolidation?

2 Min Read
Image
AnalyticsBig DataBusiness IntelligenceCollaborative DataData ManagementData QualityData VisualizationData WarehousingDecision ManagementPredictive Analytics

Descriptive, Predictive, and Prescriptive Analytics Explained

8 Min Read

Business Analytics Optimization Keynote #iod11

3 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 and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

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?