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: Decision Management and software development II – Model Driven Engineering
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 > CRM > Decision Management and software development II – Model Driven Engineering
Business IntelligenceCRMData MiningPredictive Analytics

Decision Management and software development II – Model Driven Engineering

JamesTaylor
JamesTaylor
5 Min Read
SHARE

Continuing this weeks posts on using decision management to improve development,  I thought I would post on how decision management should be part of model-driven development (model-driven engineering, a model-driven architecture or whatever).

The recent, and premature, discussion of the death of SOA led Johan den Haan to post SOA is dead; long live Model-Driven SOA in which he said:

That’s why we should talk more about the problem domain. We have to capture today’s business with formal models.

I have posted before about using decision management with MDE and answered some questions from a reader on MDE but I thought his comment was particularly pertinent to the issue of using business rules and decision management in MDE.

The key challenge, as he notes, is the problem domain and capturing today’s business. I would go further and say that we want to make capturing the problem domain as close to the solution domain as we can (so that the business users who understand what they need to do can make their software actually do it) and that we need not only…

More Read

Forrester’s Customer Experience Forum 2012
SiSense dashboard winner
Defining The Analytic Process
Watson, you know my methods… IBM moves towards HAL
Mathematics of an insurgency


Copyright © 2009 James Taylor. Visit the original article at Decision Management and software development II – Model Driven Engineering.

Continuing this weeks posts on using decision management to improve development,  I thought I would post on how decision management should be part of model-driven development (model-driven engineering, a model-driven architecture or whatever).

The recent, and premature, discussion of the death of SOA led Johan den Haan to post SOA is dead; long live Model-Driven SOA in which he said:

That’s why we should talk more about the problem domain. We have to capture today’s business with formal models.

I have posted before about using decision management with MDE and answered some questions from a reader on MDE but I thought his comment was particularly pertinent to the issue of using business rules and decision management in MDE.

The key challenge, as he notes, is the problem domain and capturing today’s business. I would go further and say that we want to make capturing the problem domain as close to the solution domain as we can (so that the business users who understand what they need to do can make their software actually do it) and that we need not only to handle today’s business but create an environment in which we can easily capture tomorrow’s also. We must handle change. In an era where most of the cost and time spent on a system will be spent in modifications not initial development, this last is crucial.

Modern systems must act – they must respond to events, keep processes moving to enable straight through processing, support busy people with no spare time and high throughput demands. Any model of such a system should model the decisions within it as first class objects to enable this. Further, these decisions – these decision services – must be easy to change and controlled by those who understand the business. After all any move by a competitor, any new regulation or policy, any new marketing initiative, any new contract will require the decision making in the system to change. If the business users who understand these drivers cannot make the changes for themselves then the result will be delay, confusion, inaccuracy, lost business and fines. Automate these decisions with business rules and all this can be addressed.

So, model-driven is certainly the future but those models should model decisions and do so explicitly and the decisions should be described using business rules so they can be managed and evolved.


Link to original post

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

When Data Flows Faster Than It Can Be Processed

10 Min Read

Critics of carbon capture and storage (CCS) often deride the…

2 Min Read

Online to Offline Conversions

8 Min Read

Guest Post: Si Chen on Cloud Computing and Open Source

11 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 chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data 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?