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Data Warehousing and Data Mining

notes

13.1.3 preparing Data for analysis with oLap server

After data is imported into the Data Warehouse SQL Server database, it must be prepared for
analysis so business managers can run reports against it. To prepare data for reporting, the system
administrator runs a DTS task that exports a selected subset of data from the SQL Server database
to the OLAP database. In the OLAP database, the data is stored in multidimensional cubes.
By storing data in OLAP cubes, instead of in relational tables in SQL Server, the Data Warehouse
can retrieve data for reporting purposes more quickly. The data can be retrieved from the cubes
faster because it is aggregated. That is, data that belongs together is already associated so it is
easier to retrieve than searching an entire relational database for the smaller parts. For example,
using OLAP server you can run a report that lists users who visit your site based on the time of
their visit and on the ASP page that they access first. It would be extremely difficult to run such
a report against a large SQL Server database.
In multidimensional cubes, data is grouped in two kinds of structures:
1. Measures: The numeric values that are analyzed.
2. Dimensions: A business entity, such as color, size, product, or time. For example, you
would use the color dimension to contrast how many red products and blue products were
sold, the size dimension to contrast how many large and small products were sold.

It is the relationship between the dimension (for example, color) and measure (for example,
number of products sold) structures that provides the basis for your reports about user activity.

248 LoveLy professionaL university