Difference between revisions of "Entities and Attributes"
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===Many people unfamiliar with database design principles often ask, “Why not just put all the data in one big table?” This single-table approach leads to problems of data redundancy (duplication) and data anomalies (data inconsistencies).=== | ===Many people unfamiliar with database design principles often ask, “Why not just put all the data in one big table?” This single-table approach leads to problems of data redundancy (duplication) and data anomalies (data inconsistencies).=== | ||
===To avoid these data issues, database normalization is used to create a design that reduces or eliminates data redundancy and, therefore, avoids data anomalies. In general, normalization helps database designers determine which attributes, or fields, belong to each entity. In turn, this information helps determine which fields belong in each table. Normalization is a multistage process that enables designers to take the raw data to be collected about an entity and develop the data into a structured, normalized form that reduces the risks associated with data redundancy. Data redundancy poses a special problem in databases because storing the same data in different places can cause problems when updates or changes to data are required.=== | ===To avoid these data issues, database normalization is used to create a design that reduces or eliminates data redundancy and, therefore, avoids data anomalies. In general, normalization helps database designers determine which attributes, or fields, belong to each entity. In turn, this information helps determine which fields belong in each table. Normalization is a multistage process that enables designers to take the raw data to be collected about an entity and develop the data into a structured, normalized form that reduces the risks associated with data redundancy. Data redundancy poses a special problem in databases because storing the same data in different places can cause problems when updates or changes to data are required.=== | ||
===value. When a record contains repeating groups (that is, multiple entries for a single column), it’s considered unnormalized. First-normal form (1NF) indicates that all values of the columns are atomic—meaning they contain no repeating values. To convert records to 1NF, remove the repeating values by making each author entry a separate record,=== | |||
Revision as of 17:36, 9 September 2017
- Conceptual model: A data model, usually represented by an entity relationship diagram (ERD)
- The client dream would be the conceptual model
- Physical model: A design for an object (a car, a house, a database, etc) which includes implementation details such as size, volume, weight, etc)
- The physical reality will become the physical model
- All many-to-many relationships must be reduced to a set of on-t--many relationships
Database Normalization
Storing data in a normalized format means only one update is required to reflect the new address, and it should always be the one that appears whenever your mailing address is needed.