Question

What were the benefits of implementing an EDW at Isle? Can you think of other potential benefits that were not listed in the case?

What are ROLAP, MOLAP, and HOLAP? How do they differ from OLAP?

Answer 1

What were the benefits of implementing an EDW at Isle? Can you think of other potential benefits that were not listed in the case?
Answer:----------
The implementation of EDW brought several benefits related to the timeliness and detail of the data that became available. Instead of five week-old monthly reports, managers can now study a variety of daily, weekly, and monthly reports. The reports segment data by particular properties and customer groups, so managers can zero in on particular problems and successes, easily making comparisons among properties. Managers can submit queries about data sets and receive information within minutes. In this way, managers can find out how particular promotions are affecting customer behavior at particular casinos. The EDW also connects data about casino activity with data about customers’ use of hotels and efforts by Isle’s hosts. This, too, helps the company target promotions and offer customers incentives they value. Even decisions as detailed as where to locate slot machines can be adjusted to boost profits based on data from the EDW.

What are ROLAP, MOLAP, and HOLAP? How do they differ from OLAP?
Answer:------
Online analytical processing (OLAP) systems-------which have their roots in decision support systems (DSSs) and executive information systems (EISs)--store data in multidimensional databases. OLAP products are particularly useful for time-series analyses and recursive calculations.
Vendors offer a variety of OLAP products that you can group into three categories:

• relational OLAP (ROLAP)
• multidimensional OLAP (MOLAP)
• hybrid OLAP (HOLAP).

ROLAP products adapt traditional relational databases to support OLAP. Vendors often use a star schema structure to extend and adapt an underlying relational database as an OLAP server.

MOLAP products provide multi-dimensional analyses of data by putting data in a cube structure. Most successful MOLAP products use a multicube approach in which a series of small, dense, pre-calculated cubes make up a hypercube.

HOLAP products combine MOLAP and ROLAP. With HOLAP products, a relational database stores most of the data. A separate multi-dimensional database stores the most dense data, which is typically a small proportion of the data.