A logical data model is a model that is not specific to
a database that describes things about which an organization wants
to collect data, and the relationships among these things.
A logical model contains representations of entities and attributes,
relationships, unique identifiers, subtypes and supertypes, and constraints
between relationships. A logical model can also contain model objects
or reference one or more models. After the logical objects and relationships
are defined in a logical data model, you can use the workbench to
transform the logical model into a database-specific physical representation
in the form of a physical data model.
Logical model objects are always contained in a root package object.
There is always one root package, but you can add additional packages
under the root package to group similar objects together.
Logical data models address the following areas of interest:
- Validating application models against business requirements
- Creating requirements for physical data models and database design
- Identifying business entities and the relationships between the
entities
Logical data models create a single view of all data. You can create
a logical data model to address performance, consistency, and redundancies
in your data. You use the logical data model to create a physical
data model that accesses the data.
When you create a logical data model, you use the following steps:
- Identify entities, attributes, and relationships:
- Review documentation for the project. You should define the scope
of the project and information about the source system where you are
getting your data. Define business requirements, process models, profiles,
architectural designs, and data models.
- Create general categories that represent the information that
you will store in the data warehouse. Make sure that interested business
analysts and subject matter experts are involved. These categories
should represent business concepts, not just attributes or subsets
of data.
- Identify the entities. Entities generalize the concepts, involved
parties, products, arrangements, locations, or events that will be
stored in the database. Entities can be objects in the database or
categories that you created above.
- Determine the relationships between the entities. Entities can
have multiple relationships with other entities, but only one relationship
exists between two entities. When you create relationships, create
them from the point of view of the business. Create names for each
side of the relationship.
- Identify the cardinality of each relationship.
- Identify the attributes and characteristics of each entity. You
should define primary keys during this step. A primary key is a subset
of attributes that uniquely identify an entity.
- Create text descriptions for entities and attributes. The description
should represent the objects from the point of view of the business.
- Merge the functional model with the logical data model.
- Create, read, update, and delete attributes in the entities.
- Maintain the relationships and cardinalities in the logical data
model and the values of the attributes.
- Validate the logical data model against the requirements of the
business. Make sure that the following information is in place in
the logical data model:
- All necessary business process are documented through entities
- All necessary data is included in the logical data model
- All entities are named, and all entities have primary keys, attributes,
and relationships with other entities in the logical data model
- The cardinalities between objects reflect their proper relationships
- Each entity and attribute is found in the data warehouse and are
related to functions or process that occur in the data warehouse
Review your data model throughout the process. Keep in mind that
you need to stay within the scope of the needs of the business, and
you should modify the model as you learn more about the needs of the
business. After the data model has been completed, continue to revise
and enhance the model to get the most benefit from the data that is
available for your business.