Databases Reference
In-Depth Information
ExampleDataSet
Suppose the following dataset is used by the FCC to keep track of amateur radio license information.
Included in this information are things like the Class of license, Callsign of operators, Frequency
privileges, and so on. See Table 8-1 below.
Table 8-1: Example Data
Examiner
Frequency
Region
Name Callsign Examiner Callsign
LicenseClass
1 ... n
Region
Coordinator
Bob
KE4IOR Ted
A4GH
Amateur Extra 3, 7, 14, 20, 28, 30 Southeast
Jim
Mike KF4DGK John
W4NBV
Technician
3, 7, 14
Southeast
Jim
Billy N4UF
Steve
WA4B
Amateur Extra 3, 7, 14, 20, 28, 30 Southeast
Jim
David K2NXT
Sam
K5RTY
General
3, 7, 14, 20
Northeast Bill
Emily W5TX
James
N1ZZT
Advanced
3, 7, 14, 20, 28
Southwest
Jim
Ray W9UTQ Jane
W0FDK
General
3, 7, 14, 20
Northwest Carol
Anomalies
The data anomalies that can occur are broken down into several different categories.
Redundancy: In the sample notice that the License Class and Region are repeated for the
corresponding LicenseClass.
Insert anomaly: This occurs because the table in which a row should be inserted can't accept the
insert. Using the sample dataset, suppose the FCC wants to create a new class of license called
Novice . A row cannot be inserted until someone is actually issued a Novice license.
Update anomaly: The same information is repeated on multiple rows, which opens the door for
updates that might result in data inconsistencies. Suppose David upgrades his license class from
General to Advanced. Changing David's LicenseClass to Advanced will cause the data to show
that the Advanced class has two different privileges. Another variation of an update anomaly
occurs when a change needs to be made to all rows, but for some reason the update operation
doesn't completely succeed. Suppose you want to change the region coordinator from Jim to
Jason. If the update operation is entirely successful then some rows would have both Jim
and Jason as section coordinators. In either case, interrogating the table to find a particular
privilege or region coordinator would result in multiple values (and it is usually impossible to
determine which value is correct).
Deletion anomaly: Deleting data that represents one piece of information requires the
deletion of other data that represents a different piece of information. Suppose the FCC decides
to discontinue the General license class. Deleting the rows in the sample will cause a loss of
operator names, callsigns, and other information where the license class equals General. Thus,
data that is unrelated to the license class is lost.
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