The language of competitive intelligence: Part two

✍ Scribed by Vernon Prior

• Publisher: John Wiley and Sons
• Year: 1998
• Weight: 42 KB
• Volume: 9
• Category: Article
• ISSN: 1058-0247
• DOI: 10.1002/(sici)1520-6386(199807/09)9:3<78::aid-cir13>3.0.co;2-1

✦ Synopsis

This is the second in a series of four articles comprising a suggested glossary of business intelligence terms. Once again, I would ask you to comment, suggest amendments, or make further contributions to produce a comprehensive glossary that is acceptable to the competitive (or business) intelligence community.

Some of the terms are of my own invention; many more have been adopted or adapted to accommodate the project.

Data consist of unconnected facts, numbers, names, codes, formulas, statements, dates, and other items of that nature.

Data mining is the systematic computer analysis of large volumes of collected data with the aim of revealing previously unidentified patterns and relationships about customers, products, services, and other activities that can lead to new and profitable business opportunities. Datamining techniques usually incorporate algorithms for performing phrase-frequency and phrase-proximity analysis. Examples of applications include: identifying new customers, confirming suitable loan applicants, revealing tax fraud, or indicating potentially rewarding investments.

Data warehouse is a repository of operational data from one or more sources within an organization that have been arranged into meaningful information, and rendered easily accessible by non-technical staff to allow for effective decision-making.