![]() 3NF design has a long heritage in online transaction processing (OLTP) systems. Third Normal Form design seeks to minimize data redundancy and avoid anomalies in data insertion, updates and deletion. It is also applicable to the various common physical schema modeling techniques found in data warehousing environments, namely normalized (3NF) schemas in Enterprise Data Warehousing environments, star or snowflake schemas in data marts, or hybrid schemas with components of both of these classical modeling techniques. In a physical design, this is usually a primary key.Įntity-relationship modeling is purely logical and applies to both OLTP and data warehousing systems. A unique identifier is something you add to tables so that you can differentiate between the same item when it appears in different places. To ensure that your data is consistent, you must use unique identifiers. In relational databases, an attribute maps to a column. An attribute is a component of an entity that helps define the uniqueness of the entity. In relational databases, an entity often maps to a table. An entity represents a chunk of information. The process of logical design involves arranging data into a series of logical relationships called entities and attributes. Entity-relationship modeling involves identifying the things of importance (entities), the properties of these things (attributes), and how they are related to one another (relationships). One technique you can use to model your organization's logical information requirements is entity-relationship modeling. You deal only with defining the types of information that you need. You do not deal with the physical implementation details yet. In addition, a well-planned design allows for growth and changes as the needs of users change and evolve.īy beginning with the logical design, you focus on the information requirements and save the implementation details for later.Ī logical design is conceptual and abstract. However, end users might not know what they need until they see it. End users typically want to perform analysis and look at aggregated data, rather than at individual transactions. ![]() Orient your design toward the needs of the end users. In the physical design, you look at the most effective way of storing and retrieving the objects as well as handling them from a transportation and backup/recovery perspective. In the logical design, you look at the logical relationships among the objects. The logical design is more conceptual and abstract than the physical design. The frequency with which data is refreshed ![]() The system environment supporting your data warehouse Relationships within and between groups of data To do so, you create the logical and physical design for the data warehouse. Now you need to translate your requirements into a system deliverable. You have defined the business requirements and agreed upon the scope of your business goals, and created a conceptual design. Your organization has decided to build an enterprise data warehouse.
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