Essay
Consider the following relational database for Grand Travel Airlines.
Grand Travel Airlines has to keep track of its flight and airplane history. A flight is uniquely identified by the combination of a flight number and a date. Every passenger who has flown on Grand Travel has a unique passenger number. For a particular passenger who has taken a particular flight, the company wants to keep track of the fare that she paid for it and the date that she made the reservation for it. Clearly, a passenger may have taken many flights (he must have taken at least one to be in the database) and every flight has had many passengers on it.
A pilot is identified by a unique pilot (or employee) number. A flight on a particular date has exactly one pilot. Each pilot has typically flown many flights but a pilot may be new to the company, is in training, and has not flown any flights, yet. Each airplane has a unique serial number. A flight on a particular date used one airplane. Each airplane has flown on many flights and dates, but a new airplane may not have been used at all, yet.
PILOT Relation
FLIGHT Relation
PASSENGER Relation
RESERVATION Relation
AIRPLANE Relation
a. Design a multidimensional database using a star schema for a data warehouse for the Grand Travel Airlines business environment. The subject will be "reservation" which represents a particular passenger reservation on a particular flight. Be sure to keep track of the fare that the passenger paid for the flight and the date of the reservation.
b. Describe three OLAP uses of this data warehouse.
c. Describe one data mining use of this data warehouse.
Correct Answer:

Verified
a. The fact table will be RESERVATION. D...View Answer
Unlock this answer now
Get Access to more Verified Answers free of charge
Correct Answer:
Verified
View Answer
Unlock this answer now
Get Access to more Verified Answers free of charge
Q37: Legacy DSS applications were not oriented towards
Q38: Data enrichment is the process of copying
Q39: A data mart is a small-scale data
Q40: Data warehouse data cannot be aggregated.
Q41: All of the following are desirable types
Q43: Data warehouse data is time variant or
Q44: In the star schema design, the dimensions
Q45: Usually, one of the dimensions of a
Q46: Data loading takes place after data transformation
Q47: Due to the nature of DSS applications,