A flight data warehouse for a travel agent consists of six dimensions: traveler, departure (city), departure_time, arrival, arrival_time, and fight; and two measures: count ( ) and avg_fare( ), where avg_fare ( ) stores the concrete fare at the lowest level but the average fare at other levels.

a. Suppose the cube is fully materialized. Starting with the base cuboid [traveler, departure, departure_time, arrival, arrival_time, flight], what specific OLAP operations (e.g., roll-up flight to airline) should one perform to list the average fare per month for each business traveler who flies American Airlines (AA) from Los Angeles in 2009?
b. Suppose we want to compute a data cube where the condition is that the minimum number of records is 10 and the average fare is over \(\$ 500\). Outline an efficient cube computation method (based on common sense about flight data distribution).