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Data Modeling - Analysis or Design?
Results of a Survey based on Lawson's Characterisation of Design, including a comparison with Architects and Accountants
This questionnaire addressed the question "Is data modelling better characterised as analysis or design" and was based on characteristics of design identified by Lawson ("How Designers Think", 3rd Edition, Architectural Press, 1997, pp121-127). The questionnaire was also given to architects and accountants, with the wording of the questions slightly changed to reflect the different terminololgy. Respondents were asked to indicate their level of agreement with each statement on a scale of 1-5: 1=Strongly Disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Strongly Agree. Values are averages across all questionnaires returned.
Sample sizes:
Data Modellers: 266
Architects: 21
Accountants:38
Database Designers (DBAs): 28
| Question |
DBAs |
Data Modellers |
Architects |
Accoun-tants |
1. The most difficult part of data modeling is understanding the business requirements. |
4.32 |
3.90 |
2.95 |
3.03 |
2. Data modeling problems are often full of uncertainties about objectives and relative priorities. |
3.70 |
3.53 |
3.52 |
3.32 |
3. Many requirements do not emerge until some attempt has been made at developing a model. |
4.29 |
4.11 |
4.00 |
3.74 |
4. Objectives and priorities are likely to change during the modeling process. |
4.22 |
3.99 |
4.05 |
3.50 |
5. In establishing requirements for a data model, something that seems important to one data modeler may not seem important to another data modeler. |
3.70 |
3.53 |
3.90 |
3.58 |
6. In establishing requirements for a data model, something that seems important to one business stakeholder may not seem important to another business stakeholder. |
4.18 |
4.24 |
4.19 |
4.13 |
7. Modeling problems are often symptoms of higher level problems. |
3.46 |
4.03 |
3.48 |
3.84 |
8. Business requirements are often negotiable. |
3.11 |
3.29 |
3.57 |
2.89 |
9. Most data modeling problems have a single correct solution. |
1.71 |
1.67 |
1.57 |
2.68 |
10. In most practical business situations, there is a wide range of possible (and workable) data models. |
3.70 |
3.64 |
4.10 |
2.92 |
11. Data modeling almost invariably involves compromise. |
3.85 |
3.74 |
3.86 |
2.92 |
12. Data modelers will almost invariably appear wrong in some ways to some people. |
3.89 |
3.64 |
3.67 |
3.74 |
13. It is usually possible to dissect a data model and identify which piece of the model supports each piece of the business requirements. |
2.69 |
3.23 |
3.10 |
2.89 |
14. I frequently re-use patterns (structures) from other data models that I have developed myself. |
3.74 |
3.49 |
3.43 |
3.53 |
15. I frequently re-use patterns (structures) that I have seen in models developed by others. |
3.5 |
3.41 |
2.86 |
3.24 |
16. There is an infallible correct process that (if properly followed) will always produce a sound data model. |
2.93 |
2.48 |
2.19 |
3.08 |
17. Identifying the end of the data modeling process (i.e. when to stop modeling) requires experience and judgment. |
3.61 |
3.78 |
3.71 |
3.68 |
18. When I am developing a data model, I sometimes produce more than one workable solution, and then choose the best one. |
3.41 |
3.06 |
3.81 |
1.82 |
19. I do not start modeling until I have a thorough understanding of business requirements. |
2.93 |
2.64 |
2.95 |
2.97 |
20. Sometimes, even when I understand the business requirements, I find it difficult to produce a data model. |
3.11 |
3.09 |
2.95 |
2.55 |
21. Data modeling requires a high level of creative thinking. |
3.52 |
3.79 |
4.10 |
3.05 |
22. I have experienced “eureka” moments (sudden and dramatic insights or solutions to problems) in my data modeling work. |
4.07 |
3.68 |
3.95 |
3.89 |
23. I find it easy to remain dispassionate and detached in my data modeling work. |
3.00 |
2.15 |
2.52 |
2.87 |
24. Data modeling is descriptive rather than prescriptive. |
3.37 |
3.00 |
3.33 |
2.92 |
25. The final data model is often a result of compromise decisions made on the basis of inadequate information. |
3.52 |
3.24 |
2.86 |
2.79 |
Click on the topics below to view other results
Summary of Surveys, Interviews and Experiments
What is Data Modelling? (Survey Results) posted 2nd December 2004
What goes Where? Perceptions of Stages in the Data Modelling Process posted 4th February 2005 |
