Database Reference
In-Depth Information
Conceptual data modeling is the process of capturing the satellite view of the business re-
quirements. What problems does the business need to solve? What do these ideas or con-
cepts mean? How do these concepts relate to each other? What is the scope of the effort?
These are types of questions that get addressed during conceptual data modeling.
The end result of the conceptual data modeling phase is a conceptual data model (CDM)
that shows the key concepts needed for a particular application development effort. This
chapter defines a concept and offers an explanation of the importance of conceptual data
modeling. We'll walk through a simple five-step, template-driven approach that works well
with MongoDB.
C
ONCEPT
E
XPLANATION
A concept is a key idea that is both
basic
and
critical
to your audience. “Basic” means this
term is probably mentioned many times a day in conversations with the people who are the
audience for the model, which includes the people who need to validate the model as well
as the people who need to use the model. “Critical” means the business would be very dif-
ferent or non-existent without this concept.
The majority of concepts are easy to identify and include those that are common across
industries such as
Customer
,
Employee
, and
Product
. An airline may call a
Customer
a
Passenger
, and a hospital may call a
Customer
a
Patient
, but in general they are all
people who receive goods or services. Each concept will be shown in much more detail at
the logical and physical phases of design. For example, the
Customer
concept might en-
compass the logical entities
Customer
,
Customer Association
,
Customer Demograph-
ics
,
Customer Type
, and so on.
Many concepts, however, can be more challenging to identify as they may be concepts to
your audience but not to others in the same department, company, or industry. For example,
Account
would most likely be a concept for a bank and for a manufacturing company.
However, the audience for the bank conceptual data model might also require
Checking
Account
and
Savings Account
to be within scope, whereas the audience for the manufac-
turing conceptual data model might, instead, require
General Ledger Account
and
Ac-
counts Receivable Account
to be within scope.
The main reason for conceptual data modeling is to get the “big picture” and understand
the scope and high level needs of the project. Aligning on a common understanding at this
level leads to these benefits:
