Database Reference
In-Depth Information
your data model will support, and to determine how your data model helps
meet those needs. During the initial round of project meetings, as well as
during interviews, listen for key words such as response time, reporting,
improve work flow, cut costs, and so on. These words and phrases are key
indicators that you are talking about the needs to be addressed by the proj-
ect. From a data modeling perspective, you may be responsible for imple-
menting the business logic enforcing certain rules about the data, or you
may be responsible for helping to determine supporting data (and objects)
that may not be immediately evident.
It's critical that all your design decisions align with the end goal of the
project. Often, this means knowing the limitations of your technology and
understanding how that technology relates to the business.
Balancing Technical Limitations with Business Needs
Now that you've identified all the areas where your design can help the or-
ganization, it's time to temper ambition with a touch of pragmatism. As
information technology and information systems specialists, we tend to fol-
low the latest and greatest in hardware, software, and design and develop-
ment techniques. A large part of our careers is based on our ability to learn
new technology, and we like to incorporate everything we've learned into
our projects. Similarly, businesspeople (owners, analysts, users) want their
applications to do everything, be everything, and solve every problem,
without ever throwing an error. Unfortunately, the temptation to use
everything we know to meet the highest expectations can lead to almost
uncontrollable scope creep in a design project.
To balance what can be done against what needs to be done, you need
to engage in a little bit of prioritization. Once you have the list of require-
ments, the data from the interviews, and so on, you need to decide which
tasks are central to the project and determine the priority of each task.
Gathering Usage Data
Now it's time to look at the performance-related data you need in order to
successfully design a functional, scalable data model. Although it's not
technically a part of the core data model design, it's worthwhile to begin
 
 
 
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