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Microsoft Access. Removing Redundancy in a Database. Objectives. Identify repeated data Identify related information Redundant data anomalies Removing redundancy. Identifying Repeated Data.
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Microsoft Access Removing Redundancy in a Database
Objectives • Identify repeated data • Identify related information • Redundant data anomalies • Removing redundancy
Identifying Repeated Data • Repeated data for person with ID Number 93500 has to be kept in this table, in order to track amount paid and transaction date • Some repeated data may seem redundant (for example, Transaction Date). But should actually be treated as separate fields
Identifying Related Information • ID Number and Name data describe information relevant to a person. Thus, ID Number and Name with (93500, Phillip Doe), should to kept in a Persons table • The Amount Paid and Transaction Date describe transaction data, and should be kept in a Transactions table, linked to the Persons table through the ID Number
Redundant Data Anomalies • Redundant databases can have modifications anomalies: • Update anomaly • Insertion anomaly • Deletion anomaly
Update Anomaly • Update to an employee’s address information did not fully complete • The same employee has conflicting address information
Insertion Anomaly • Suppose a table stores information about faculty and their courses • New faculty that has not been assigned to teach any courses, cannot be inserted into the database
Deletion Anomaly • When the faculty member temporarily stops teaching the course assigned, the entire record –including information about the faculty– has to be deleted
Removing Redundancy • “Normalization” increases efficiency by eliminating redundant data, while ensuring that only related data are kept together • Separate tables are kept for each group of related data • Sets of related data are uniquely identified with a primary key • Relationships between tables are established via link fields