Data modeling is the analysis of data objects that are used
in a business or other context and the identification of the relationships
among these data objects. Data modeling is a first step in doing
object-oriented programming.
Data modeling is the formalization
and documentation of existing processes and events that occur during
application software design and development. Data modeling techniques and tools
capture and translate complex system designs into easily understood
representations of the data flows and processes, creating a blueprint
for construction and/or re-engineering.
A data model can be thought of as
a diagram or flowchart that illustrates the relationships between
data. Although capturing all the possible relationships in a data model can be
very time-intensive, it's an important step and shouldn't be rushed.
Well-documented models allow stake-holders to identify errors and make changes before any
programming code
has been written.
Data modelers often use multiple
models to view the same data and ensure that all processes, entities,
relationships and data flows have been identified. There are several
different approaches to data modeling, including:
Conceptual Data Modeling - identifies the
highest-level relationships between different entities.
Enterprise Data Modeling - similar to conceptual
data modeling, but addresses the unique requirements of a specific business.
Physical
Data Modeling - represents
an application and database-specific implementation of a logical data model.
Logical Data Modeling - illustrates the specific
entities, attributes and relationships involved in a business function. Serves
as the basis for the creation of the physical data model.
No comments:
Post a Comment