I was teaching a data modeling class a few weeks back, and we were in the middle of building subject area models when one of the participants called me over to look at her manufacturing model. There was an entity called Production that represented the entire production process required to transform raw materials into finished products. Although data and process both need to be understood and validated for the complete requirements picture, process entities do not belong on a data model. This Production process entity will need to get replaced with entities such as Plant and Raw Material.
We tried several techniques during the training to change this participants thinking from process to data, and the one that worked best was to think of the world in terms of nouns instead of actions.
Are there other techniques that you have used with success to help get people thinking data instead of process? Please share!
Common across the suggested techniques was the theme of focusing on the audience and to first understand the world from their perspective. It is not surprising that several Challengers recommended first modeling the process, then the data. Others recommended explaining the deliverables of the application in terms of reports and screens to distinguish the difference.
There were also a number of other useful techniques, including illustrating the data and process distinction using familiar concepts such as recipes.
Carol Lehn, data engineer, recommends making the distinction between data and process clear by first building a process decomposition diagram. Participants can do this pretty quickly when theyre thinking process, not data. I point out that the data model documents the information needed to perform the processes we just identified (as well as those we havent). Then, when someone starts to speak process during data modeling, I can literally or figuratively point to the process model and ask them if what theyre describing belongs on that model or the one were working on. Laurie McKinlay, data analyst, takes a similar approach. I would probably ask the novice modeler to break Production down into a few components. Supposing these were also processes, I would continue to ask, What do you need to know to do that? Kenneth Hansen, consultant, would develop both the process model and the data model simultaneously, showing how the processes reference or update or create data.
Reports can be used to explain the difference between data and process. Jacqueline Tomlinson, data architect, says, Focusing on reports can help them understand what needs to be stored as distinct from the processes that create the information. For example, if the user wants to be able to compare forecast amounts of Raw Materials per Plant and actual amounts of Raw Material per Plant and they want to be able to select the Plant and the Raw Material from a drop-down list, they can see that these lists need to be stored somewhere.
Other Useful Techniques
Norman Daoust, business and data analyst consultant and trainer, helps people make the shift to data by asking them for actual occurrences of the process. Having them provide actual data values helps people to focus on the data needed to support their business process. Geof Clark, enterprise engineer, and Barbara Nichols, data and metadata management consultant, use household concepts to distinguish data from process. Clark says, I think of a recipe. What do I need to have before I start cooking? What is in my cupboard, and what do I need to acquire before I start? When Im done, what will I have? Much has been said about the importance of good processes, but these are largely measured in terms of the quality of their output, which in many cases is simply data. Nichols uses banking as an example, While the process of banking has changed dramatically over the last 20 years, the data hasnt changed: debits, credits, accounts, balances, etc.
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