When designing a database, one needs to have an understanding of the needs of the data that will be stored. In other words, a designer needs to know how to abstract the real world concepts and quantities into a relatively rigid framework. In many fields, those who know the most about the real world concepts, know the least about abstracting those concepts into a data framework. Conversely, those database engineers who are experts in data storage and retrieval techniques, often know very little about the field that they are attempting to abstract, and hence, are ill-equipped to perform said abstraction. So how do these two groups perform the mind meld??
In the best cases, a dialog ensues. However, this too is not without difficulties, and I will hypothesize that these difficulties have to do with the process that a persons mind goes through when thinking of the complex task of data abstraction. Perhaps no one, the database designer or the content expert, really is trained to perform abstraction. In other words: Data abstraction confuses people. My observation of the possible causes of this state of being follow:
- People don’t provide adequate documentation and outlines when having a meeting of the minds on data abstraction
- People don’t read outlines and documentation fully
- People get overwhelmed when thinking of sorting out data: they tend to muddle hypothesis making with data collection
- Unlimited possibilities cause people to wander aimlessly
- People skip steps in their mind
Are any of these notions valid? If so, how to confront them?
to be continued…