We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Some Thoughts on Decision Terminology
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 > Some Thoughts on Decision Terminology
Business RulesDecision Management

Some Thoughts on Decision Terminology

JamesTaylor
JamesTaylor
2 Min Read
Some Thoughts on Decision Terminology
Photo by geralt on Pixabay (https://pixabay.com/photos/paragraph-law-flood-stress-burnout-3213669/)
SHARE

An interesting thread over on LinkedIn got into a discussion of terminology and I thought I would share my opinion on this here:

  • Decision Management is an approach for supporting, automating, managing and improving decisions.
    • Decision Management Systems are systems that automate and manage repeatable decisions.
    • Decision Support Systems support people manage decisions, both repeatable and one-off.
  • To build Decision Management Systems or Decision Support Systems one should engage in some decision discovery and modeling to make sure you understand the decisions involved. You can use The Decision Model or the soon to be proposed Decision Model and Notation standard but you don’t have to. These models of decisions include mapping decisions to the business events that trigger them, the business processes that need them and the business objectives/KPIs that measure their effectiveness.
  • Once you understand what you are trying to do you might apply a Decision Management platform or Business Rules Management System and you might apply some decision science or data science to build an effective Decision Service.
  • Finally you will engage in ongoing decision performance analysis and monitoring so you can keep improving your decision-making over time.

The key to all of this, of course, is a focus on decisions as well as business rules which takes us back, I think, to the original question.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article's core relationship is workload-by-workload decision-making for cloud migration, where s
Which Workloads Should Move to the Cloud?
Cloud Computing Exclusive IT
Flat editorial illustration: The article positions data governance as a strategic board-level concern rather than a purely techni
Why Data Governance Is Becoming a Board-Level Business Priority
Big Data Exclusive Policy and Governance
Flat editorial illustration: The article argues that data annotation quality should be measured by inspectable gold sets, written
The Top Data Annotation Companies Are Separated by Proof of Quality, Not Headcount
Big Data Exclusive
Flat editorial illustration: The article's core relationship is the gap between raw bank-feed records and reliable subscription i
Subscription Trackers Have a Transaction Data Problem
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

See Why Businesses Can't Do Without Customer Data Collection
AnalyticsBig DataBusiness IntelligenceCollaborative DataData ManagementData WarehousingDecision ManagementExclusiveNewsWeb Analytics

See Why Businesses Can’t Do Without Customer Data Collection

7 Min Read
Connectivity Disrupting Traditional Models: Online Peer to Peer Commerce
Business RulesMarketing

Connectivity Disrupting Traditional Models: Online Peer to Peer Commerce

5 Min Read
The Big Question In Big Data Is...What's The Question?
AnalyticsBest PracticesBig DataBusiness IntelligenceCollaborative DataData ManagementData MiningData QualityData VisualizationData WarehousingDecision ManagementPredictive AnalyticsSentiment AnalyticsSocial DataSocial Media AnalyticsSoftwareStatisticsText AnalyticsUnstructured DataWeb AnalyticsWorkforce AnalyticsWorkforce Data

The Big Question In Big Data Is…What’s The Question?

7 Min Read
The Urgent Crowds Out the Important
AnalyticsBusiness IntelligenceDecision Management

The Urgent Crowds Out the Important

7 Min Read

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

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

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?