The OLAP cube shown in Figure 33.1 has been prepared for a car rental company that rents out cars to customers throughout the UK. The company wishes to explore which manufacturer, model, engine size and trim (interior finish) generates the most rental income in each location of the UK. For example, the manufacturer Ford has various models including Mondeo, Fiesta and Ka and each model comes in various size of engine such as 1.8 or 1.6 with each available in one of three trim levels of high, medium and low.

-Describe the four common OLAP operations for querying data. Provide an example of each operation using the OLAP cube in Figure 33.1 and your answer to question 33.1.

Question

The OLAP cube shown in Figure 33.1 has been prepared for a car rental company that rents out cars to customers throughout the UK. The company wishes to explore which manufacturer, model, engine size and trim (interior finish) generates the most rental income in each location of the UK. For example, the manufacturer Ford has various models including Mondeo, Fiesta and Ka and each model comes in various size of engine such as 1.8 or 1.6 with each available in one of three trim levels of high, medium and low. 
 
-Describe the four common OLAP operations for querying data. Provide an example of each operation using the OLAP cube in Figure 33.1 and your answer to question 33.1.

Quizplus · Accepted Answer

The Answer is OLAP operations include:
Roll-up, drill-down, slice and dice, pivoting.
Roll-up performs aggregations on the data by moving up the dimensional hierarchy or by dimensional reduction e.g. 3-D to 2-D.
For example, {location, manufacturer and time} analysis of rental income to {location, manufacturer} analysis of rental income.
For example, analysis of weekly rental income to analysis of monthly rental income.
Drill-down is the reverse of roll-up and involves revealing the detailed data that forms the aggregated data. Drill-down can be performed by moving down the dimensional hierarchy or by dimensional introduction e.g. 2-D to 3-D.
For example, {location, manufacturer} analysis of rental income to {location, manufacturer and time} analysis of rental income.
For example, analysis of monthly rental income to analysis of weekly rental income.
Slice and dice - ability to look at data from different viewpoints. The slice operation performs a selection on one dimension of the data whereas dice uses two or more dimensions.
For example, a slice is analysis of rental income according to {time = '2012'} OR {manufacturer = 'Ford'} OR {location = 'London'}
For example, a dice is analysis of rental income according to {time = '2012'} and {manufacturer = 'Ford'} OR {time = '2012'} and {manufacturer = 'Ford'} and {location = 'London'}
Pivot - ability to rotate the data to provide an alternative view of the same data.

For example, analysis of rental income using the location (city) as x-axis against time (year) as the y-axis can be rotated so that time (year) is the x-axis against location (city) is the y-axis.

The OLAP Cube Shown in Figure 33