Data modeling is a process used to define and analyze data requirements needed to support the business processes. The process of data modeling involves professional data modelers working with business stakeholders, as well as potential users of the information system.
Conceptual data model:
It is a set of technology independent specifications about the data and is used to discuss initial requirements with the business stakeholders.
Logical data model:
The conceptual data model is translated into a logical data model, which documents structures of the data the can be implemented in databases. Implementation of one conceptual model may require multiple logical data models.
Physical data model:
This is the last step in data model where the logical data model is transformed into a physical data model that organizes the data into tables, and accounts for access, performance and storage details.
Data modeling not only defines data elements, but also their structures and relationships between them.
- To assist business analysts, programmers, testers, manual writers, IT package selectors, engineers, managers, related organizations, clients to understand and use an agreed semi-formal model concepts of the organization and how they related to each other.
- To manage data as a resource
- For the integration of information systems
- For designing databases/data warehouses (aka data repositories)
Erwin Data Modeler
CA Erwin Data modeler is a software tool for data modeling (data requirements analysis, database design etc.,) of custom developed information systems, including databases of transactional systems and data marts.
Erwin’s data modeling engine is based upon the IDEF1X method, although it now supports diagrams displayed with information engineering notation as well.
Conceptual data modeling
Logical data modeling
Physical data modeling
Logical to physical transformation
Includes an abbreviation/naming dictionary called “Naming standards editor” and a logical to RDBMS data type mapping facility called “Data type standards editor”, both of which are customizable with entries and basic rule enforcement
Once the database designer is satisfied with the Physical data model, the tool can automatically generate a SQL Data definition language (DDL) script that can be directly executed in a RDBMS environment or saved to a file.
If an analyst needs to examine and understand an existing data structure, ERwin will depict the physical data base objects in an Erwin model file.
Model to model comparison
The ‘complete/compare” facility allows an analyst or a designer to view the differences between two model files (including real-time reverse engineered files), for instance to understand the changes between two versions of a model.
An UNDO feature is available from version 7.
Bulk editor: CA Erwin data modeler has a unique bulk editor feature that enable users to edit a collection of objects in a single editing session.
Active Model Templates: Derive new models from template models. Change in template model can be automatically synchronized into all derived models.
API (Application programmable interface) support: Erwin provides a programming interface to automate tasks that involves reading/writing of data models.
Domains (Column names): Erwin has a concept of domains that defines the characteristics of attributes/columns in a model. It acts as a library of attributes/columns so it can be reused across entities/tables and centrally managed through a flexible property inheritance/over-ride mechanism.
Model repository and version management: Erwin has a very powerful integrated model repository for change management (Workgroup edition) that support metadata governance, versioning, multi-user modeling etc.,
Trial version of the Erwin software can be downloaded at erwin.com