Glossary

Data warehousing

The accessible storage of data into a centralised repository.

Creating and Using Data Warehouses

Data mining

Advanced data inference algorithms designed to discover relationships between seemingly unrelated data. For example, people who buy one product tend to also buy another.

Data Mining Helps Make Better Business Decisions

BI

Business Intelligence is the conversion of raw business data into crucial insights. Modern tools make heavy use of graphical environments to both simplify the usage and maximise the comprehension of the data.

Transform Data into Decisions with Business Intelligence

Cubes

An advanced way of addressing the entirety of a database’s needs. Historical reports, report definitions, the data, structures of the data, tuning analyses – everything is stored together for maximum performance.

See also OLAP.

OLAP

On Line Analytical Processing – flexible, real-time analysis that can include data mining. This lets you see the data the way you want it, when you want it. For example, you can view the monthly sales figures for a number of stores with indicators of relative performance against the previous month and the same month for the previous year.

RDBS

Relational database system – a database in which data relationships can be maintained in both directions. The easiest way to think about this is to consider a phonebook and trying to search on suburb. As the phonebook is obviously optimized for finding names and names link to a suburb value, a relational database also allows each suburb to link back to the names within it. This allows complex relationships between data items. Sales can be traced to customers and customers can be traced to sales.

Reporting

Traditional reports offer a fixed view of the business. They are different and separate from OLAP, which allows for dynamic, customised views.

Reporting Services Datasheet