Database Reference
In-Depth Information
It is also ideal to be able to import flat files, such as SQL scripts, to
generate (reverse-engineer) databases. Although you won't use this feature
a lot to generate new models, it can be helpful to start with an existing
physical model in order to generate a new logical data model. If your tool
can import the schema of a physical database, it can be a real time-saver.
Physical Modeling
Several of the available data modeling tools can not only help you generate
the logical data model but also help create a physical model for use in the
SQL Server 2008 database you are deploying to. This feature can also be
a huge time-saver during the development phase and, when used with
proper change management and source code management, can even assist
in deploying databases and managing versions of databases that are de-
ployed. In our opinion, this capability is high on the list, particularly for
larger environments.
Most data modeling tools, particularly those that advertise themselves
as enterprise class, will offer far more features than these. However, these
are the primary pieces of functionality that any data modeling tool should
offer. To make sure it meets the needs of your project or job, be sure to
thoroughly review any modeling software before buying.
Using Requirements to Build the Model
So far, this topic has been about setting the groundwork for building a data
model for a realistic scenario. We've covered everything from the basic
definition of a data model to the details of each type of data a company may
need to store. We now have all the tools necessary to begin building a data
model for Mountain View Music (we abbreviate the company name as
MVM throughout the remainder of this chapter). First, we lay out how our
various data points from the requirements gathering phase will map to the
objects we'll create in a data model. We also discuss implementing busi-
ness rules in a data model.
Entity List
When the user interviews and surveys were conducted in the requirements
gathering phase, we made sure to take notes regarding certain key words,
usually nouns, which represented the types of data that the new model
 
 
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