Data modeling is a method used to define and analyze data requirements needed to support the business processes of an organization.
The data requirements are recorded as a conceptual data model with associated data definitions. Actual implementation of the conceptual model is called a logical data model. To implement one conceptual data model may require multiple logical data models. Data modeling defines the relationships between data elements and structures.
Data modeling techniques are used to model data in a standard, consistent, predictable manner in order to manage it as a resource. The use of this standard is strongly recommended for all projects requiring a standard means of defining and analyzing the data resources within an organization.
This logical data model contains all the needed logical and physical design choices and physical storage parameters needed to generate a design in a Data Definition Language, which can then be used to create a database. A fully attributed data model contains detailed attributes for each entity.
The term database design can be used to describe many different parts of the design of an overall database system. Principally, and most correctly, it can be thought of as the logical design of the base data structures used to store the data. In the relational model these are the tables and views. In an object database the entities and relationships map directly to object classes and named relationships. However, the term database design could also be used to apply to the overall process of designing, not just the base data structures, but also the forms and queries used as part of the overall database application within the database management system (DBMS).
Should a data warehousing solution be required, It will be necessary to create a Target database in which to hold the data which is to be extracted from the Source systems. The Target Database will generally be held in a Dimensional Model format. The data being held in a denormalized format with a Star, Snowflake or hybrid structure.
Creating the Dimensional Model, usually takes the form of creating Logical/Physical models of the iterative stages through which the data will pass. These Stages may include a Cleansing Area, Staging Area and Datawarehouse Area etc. Creating Logical/physical models provides a means of mapping data relationships, utilizing lookups and getting the raw data into a Dimensional Model format. It also provides a flexible means of updating the model and incorporating future changes.