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OLAP Multidimensional

Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

Online Analytical Processing and Oracle


Now that we understand that OLAP is a tool that displays summarized data, plotting one dimension against another, let's look at the vendor implementations of this technology. As you saw in the previous section, pivot tables are an excellent way to display multidimensional data, but OLAP involves more than just the multidimensional display of information. OLAP tools also must be able to extract and summarize requested data according to the needs of an end user, and there are two approaches for this data extraction that need to be discussed.

When multidimensional OLAP was first introduced, data was extracted from the relational engine and loaded into a proprietary architecture called a multidimensional database. The data was displayed quickly by accessing the pre-summarized data. This type of OLAP utilizes a multidimensional database, which has become known as MOLAP, or multidimensional OLAP. The other approach to data extraction uses a mapping facility and extracts the raw data from an operational relational database at runtime, summarizing and displaying the data. Because this approach does not require a multidimensional database, it has become know as ROLAP, or relational OLAP.

There are many different types of OLAP and MDDB products on the market today. As shown in Table 5.5, OLAP and MDDB have their own relative advantages and disadvantages, and they are both fighting to achieve recognition for their strengths.

Trait                           ROLAP                MDDB
Speed                    Slow                Fast
Queries                  Flexible             Fixed
Disk cost                Low                 High

Table 5.5 OLAP versus MDDB.

This is an excerpt from "High Performance Data Warehousing", copyright 1997.
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