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Advantages
•Avoids data modification (INSERT/DELETE/UPDATE) anomalies as each data item lives in One place
•Greater flexibility in getting the expected data in atomic granular
•Normalization is conceptually cleaner and easier to maintain and change as your needs change
•Fewer null values and less opportunity for inconsistency
•A better handle on database security
•Increased storage efficiency
•The normalization process helps maximize the use of clustered indexes, which is the most powerful and useful type of index available. As more data is separated into multiple tables because of normalization, the more clustered indexes become available to help speed up data access
Disadvantages
•Requires much more CPU, memory, and I/O to process thus normalized data gives reduced database performance
•Requires more joins to get the desired result. A poorly-written query can bring the database down
•Maintenance overhead. The higher the level of normalization, the greater the number of tables in the database.
•Avoids data modification (INSERT/DELETE/UPDATE) anomalies as each data item lives in One place
•Greater flexibility in getting the expected data in atomic granular
•Normalization is conceptually cleaner and easier to maintain and change as your needs change
•Fewer null values and less opportunity for inconsistency
•A better handle on database security
•Increased storage efficiency
•The normalization process helps maximize the use of clustered indexes, which is the most powerful and useful type of index available. As more data is separated into multiple tables because of normalization, the more clustered indexes become available to help speed up data access
Disadvantages
•Requires much more CPU, memory, and I/O to process thus normalized data gives reduced database performance
•Requires more joins to get the desired result. A poorly-written query can bring the database down
•Maintenance overhead. The higher the level of normalization, the greater the number of tables in the database.
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