Posts Tagged ‘data models’
Written by Ronald G. Ross on November 5, 2013 . Posted in Business Rules, Rule Management, RuleSpeak, SBVR, Vocabulary
Any Elegant Solution to Our Current Business Rules Dilemma? Nooo.
I get this question all the time, and it’s a painful one, so let me answer on the record. Question: In our enterprise architecture tooling, there’s a business dimension in which we define Business Concepts (the real business language), and an IT dimension containing Information Objects (data organization model). How can we solve the problem that business expresses rules as they relate to Business Concepts, while IT needs to translate these into rules related to Information Objects? We don’t want to bother business with IT model concerns, nor duplicate the rules in two places. Can you please shed light on an elegant approach to this dilemma? My answer: The standard SBVR[1] provides the ‘elegant’ approach, which is technology that can “read” language based on the business vocabulary (e.g., RuleSpeak) and/or dialog with people to disambiguate those statements. Until such technology is commercially available – and why not, look what IBM Watson can do! – two forms of each statement are unfortunately necessary. The key for your rule management regime is to maintain traceability between them. By the way, the mapping is almost certainly 1:m, not 1:1. I wish I had a better answer, but there just is none today. All I can say is that current implementation technologies for business rules are very, very primitive. ~~~~~~~~~~~ Acks: Tom Andries www.BRSolutions.com
[1] The OMG standard Semantics of Business Vocabulary and Business Rules. See the SBVR Insider section on www.BRCommunity.com for insights about SBVR.
Written by Ronald G. Ross on January 10, 2012 . Posted in Concept Analysis, Concept Models, Data Models, Vocabulary
More on Concept Model vs. Conceptual Data Model
As part of a continuing dialog, I recently asked these questions: What does the term “conceptual data model” really mean? Is it the best term for what is meant? To me, it sounds like “conceptual data model” might be about “conceptual data”. Surely not(?). What exactly then? (Some of my thoughts on the matter: http://goo.gl/8GX5o.) A practitioner responded with the following 3-part challenge below. With each challenge is my response. Challenge part 1: Which of the following, if any, would you see in a conceptual data model: primary keys, foreign keys, abstract keys, constraints, nulls, non-nulls, 1:1s, 1:Ms, optionality, cardinality, etc.? My response: Wrong approach. Bad definition practice one three counts. 1. Things should be defined in terms of their essence, what they are, not in terms of what are allowed or disallowed. 2. Suppose none of the above were allowed. You’d end up simply with a description of what the thing is not, not what it is. Since you can’t possibly list everything it’s not, the definition is woefully incomplete. 3. The list attempts to describe something in terms of an implementation or design of the thing, not in the thing’s own terms. That’s simply backwards. Challenge part 2: So let’s turn the question around. What would be the minimum types of objects you need to explore a concept, produce a mini model, and convey knowledge about the concept and its relationship to other concepts? My response: To develop a concept you need: 1. A concise definition for the concept, which distinguishes the concept from all other concepts and conveys its essence to the business. 2. A business-friendly signifier (term) for the concept that has only that one meaning (or is properly disambiguated by context). 3. A set of facts that indicates the place of the concept within a structure of other concepts (e.g., classification, categorization). 4. A set of verbs that permits the business to communicate unambiguously about how the concept relates to other concepts (e.g., customer places order). 5. A set of structural rules for the concept and its relations to other concepts, as needed. Why the verbs? Because you can’t write sentences without verbs and business rules can always be written in sentences. ‘Requirements’ should be too(!). Challenge part 3: When you are finished do you call that a ‘conceptual data model’? My response: You notice that I didn’t say anything, directly or indirectly, about “data”. That term is irrelevant. Taking away “data” leaves “conceptual model”. But that term suggests what the model is made of (concepts), not what it is about. Of course the kind of model we’re talking about is made up of concepts – it’s certainly not made of physical material (e.g., wood, plaster, etc.) or through use of math (some formula). That leaves “concept model” (also sometimes called “fact model”). Bingo. Is there a standard for this kind of model? Indeed there is: SBVR (Semantics of Business Vocabulary and Business Rules). See the SBVR Insider section on www.BRCommunity.com for more information.
Written by Ronald G. Ross on January 9, 2012 . Posted in Data Models
Why Data Models Can’t Be Verified … and Why Data Modelers Remain Under-Empowered – Data Model Week
In the real world, we communicate with sentences … just like we are doing now. If a “data model” can’t support writing meaningful and consistent sentences, then surely something is amiss. Business rules are always sentences, so you can see where I’m going with this. So I come to this radical and provocative suspicion: The reason data models remain so often disconnected from other things in the business and IT, and why data modelers generally so under-empowered, is that data modeling practices have been removed them from direct engagement with business logic. Shouldn’t be that way. Won’t ever work well. I’m sure there are a whole lot of people who disagree with me. So I am going to write a series of posts this week on the subject … and call this ‘data model’ week.
Written by Ronald G. Ross on October 6, 2011 . Posted in Business Analysis, Business Communication, Concept Analysis, Concept Models, Data Models, Vocabulary
Something Important All Business Analysts Owe to Business People … Probably Not Something You’d Expect?
One of the first rules of business analysis should be never waste business people’s time. One of the fastest ways to waste their time is not knowing what they are talking about … literally … and do nothing about it. So you end up just wasting their time over and over again. Unacceptable. Is there a way to avoid it? Yes, by taking the time to understand exactly what concepts the business people mean when they use the words they use. I believe business vocabulary should be job one for Business Analysts. If you don’t know (and can’t agree about) what the concepts mean, then (excuse me here for being blunt) you simply don’t know what you’re talking about. (And sometimes, unfortunately, neither do the business people … which is something important BAs should find out as early as possible.) So structured business vocabularies (fact models) are a critical business analysis tool. How else is there to analyze and communicate about complex know-how in a process-independent way?! Looking at the issue the other way around, you can make yourself look really smart about a complex area in a relatively short time by having and following a blueprint. We’ve had that experience many, many times in a wide variety of industries and problem areas. (Try jumping between insurance, pharmaceuticals, electricity markets, eCommerce, race care equipment, credit card fraud, trucking, taxation, healthcare, banking, mortgages, pension administration, ship inspections, and more! We do.) There’s no magic to it – like contractors for the construction of buildings, you must have or create structural blueprints. For operational business know-how, that means bringing an architect’s view to structure the concept system of the problem space … just a fancy way of saying develop a well-structured business vocabulary. Then a whole lot of things will fall right into place for you. P.S. By the way, I’m not talking about any form of data modeling here. Also, there’s no real need to use the ‘S’ word (semantics) for it.
Posts Tagged ‘data models’
Written by Ronald G. Ross on November 5, 2013 . Posted in Business Rules, Rule Management, RuleSpeak, SBVR, Vocabulary
Any Elegant Solution to Our Current Business Rules Dilemma? Nooo.
I get this question all the time, and it’s a painful one, so let me answer on the record. Question: In our enterprise architecture tooling, there’s a business dimension in which we define Business Concepts (the real business language), and an IT dimension containing Information Objects (data organization model). How can we solve the problem that business expresses rules as they relate to Business Concepts, while IT needs to translate these into rules related to Information Objects? We don’t want to bother business with IT model concerns, nor duplicate the rules in two places. Can you please shed light on an elegant approach to this dilemma? My answer: The standard SBVR[1] provides the ‘elegant’ approach, which is technology that can “read” language based on the business vocabulary (e.g., RuleSpeak) and/or dialog with people to disambiguate those statements. Until such technology is commercially available – and why not, look what IBM Watson can do! – two forms of each statement are unfortunately necessary. The key for your rule management regime is to maintain traceability between them. By the way, the mapping is almost certainly 1:m, not 1:1. I wish I had a better answer, but there just is none today. All I can say is that current implementation technologies for business rules are very, very primitive. ~~~~~~~~~~~ Acks: Tom Andries www.BRSolutions.com
[1] The OMG standard Semantics of Business Vocabulary and Business Rules. See the SBVR Insider section on www.BRCommunity.com for insights about SBVR.
Written by Ronald G. Ross on January 10, 2012 . Posted in Concept Analysis, Concept Models, Data Models, Vocabulary
More on Concept Model vs. Conceptual Data Model
As part of a continuing dialog, I recently asked these questions: What does the term “conceptual data model” really mean? Is it the best term for what is meant? To me, it sounds like “conceptual data model” might be about “conceptual data”. Surely not(?). What exactly then? (Some of my thoughts on the matter: http://goo.gl/8GX5o.) A practitioner responded with the following 3-part challenge below. With each challenge is my response. Challenge part 1: Which of the following, if any, would you see in a conceptual data model: primary keys, foreign keys, abstract keys, constraints, nulls, non-nulls, 1:1s, 1:Ms, optionality, cardinality, etc.? My response: Wrong approach. Bad definition practice one three counts. 1. Things should be defined in terms of their essence, what they are, not in terms of what are allowed or disallowed. 2. Suppose none of the above were allowed. You’d end up simply with a description of what the thing is not, not what it is. Since you can’t possibly list everything it’s not, the definition is woefully incomplete. 3. The list attempts to describe something in terms of an implementation or design of the thing, not in the thing’s own terms. That’s simply backwards. Challenge part 2: So let’s turn the question around. What would be the minimum types of objects you need to explore a concept, produce a mini model, and convey knowledge about the concept and its relationship to other concepts? My response: To develop a concept you need: 1. A concise definition for the concept, which distinguishes the concept from all other concepts and conveys its essence to the business. 2. A business-friendly signifier (term) for the concept that has only that one meaning (or is properly disambiguated by context). 3. A set of facts that indicates the place of the concept within a structure of other concepts (e.g., classification, categorization). 4. A set of verbs that permits the business to communicate unambiguously about how the concept relates to other concepts (e.g., customer places order). 5. A set of structural rules for the concept and its relations to other concepts, as needed. Why the verbs? Because you can’t write sentences without ver
bs and business rules can always be written in sentences. ‘Requirements’ should be too(!). Challenge part 3: When you are finished do you call that a ‘conceptual data model’? My response: You notice that I didn’t say anything, directly or indirectly, about “data”. That term is irrelevant. Taking away “data” leaves “conceptual model”. But that term suggests what the model is made of (concepts), not what it is about. Of course the kind of model we’re talking about is made up of concepts – it’s certainly not made of physical material (e.g., wood, plaster, etc.) or through use of math (some formula). That leaves “concept model” (also sometimes called “fact model”). Bingo. Is there a standard for this kind of model? Indeed there is: SBVR (Semantics of Business Vocabulary and Business Rules). See the SBVR Insider section on www.BRCommunity.com for more information.
Written by Ronald G. Ross on January 9, 2012 . Posted in Data Models
Why Data Models Can’t Be Verified … and Why Data Modelers Remain Under-Empowered – Data Model Week
In the real world, we communicate with sentences … just like we are doing now. If a “data model” can’t support writing meaningful and consistent sentences, then surely something is amiss. Business rules are always sentences, so you can see where I’m going with this. So I come to this radical and provocative suspicion: The reason data models remain so often disconnected from other things in the business and IT, and why data modelers generally so under-empowered, is that data modeling practices have been removed them from direct engagement with business logic. Shouldn’t be that way. Won’t ever work well. I’m sure there are a whole lot of people who disagree with me. So I am going to write a series of posts this week on the subject … and call this ‘data model’ week.
Written by Ronald G. Ross on October 6, 2011 . Posted in Business Analysis, Business Communication, Concept Analysis, Concept Models, Data Models, Vocabulary
Something Important All Business Analysts Owe to Business People … Probably Not Something You’d Expect?
One of the first rules of business analysis should be never waste business people’s time. One of the fastest ways to waste their time is not knowing what they are talking about … literally … and do nothing about it. So you end up just wasting their time over and over again. Unacceptable. Is there a way to avoid it? Yes, by taking the time to understand exactly what concepts the business people mean when they use the words they use. I believe business vocabulary should be job one for Business Analysts. If you don’t know (and can’t agree about) what the concepts mean, then (excuse me here for being blunt) you simply don’t know what you’re talking about. (And sometimes, unfortunately, neither do the business people … which is something important BAs should find out as early as possible.) So structured business vocabularies (fact models) are a critical business analysis tool. How else is there to analyze and communicate about complex know-how in a process-independent way?! Looking at the issue the other way around, you can make yourself look really smart about a complex area in a relatively short time by having and following a blueprint. We’ve had that experience many, many times in a wide variety of industries and problem areas. (Try jumping between insurance, pharmaceuticals, electricity markets, eCommerce, race care equipment, credit card fraud, trucking, taxation, healthcare, banking, mortgages, pension administration, ship inspections, and more! We do.) There’s no magic to it – like contractors for the construction of buildings, you must have or create structural blueprints. For operational business know-how, that means bringing an architect’s view to structure the concept system of the problem space … just a fancy way of saying develop a well-structured business vocabulary. Then a whole lot of things will fall right into place for you. P.S. By the way, I’m not talking about any form of data modeling here. Also, there’s no real need to use the ‘S’ word (semantics) for it.