Modern database technology for intelligence management in a Network-Enabled Defence - anintroduction


  • Per Svensson

Publish date: 2008-10-02

Report number: FOI-R--2568--SE

Pages: 52

Written in: Swedish


  • intelligence management
  • analysis support
  • decision support
  • vertical databases


This report was commissioned by the FOI research project "Situation and threat analysis for the Nordic Battle Group 2011". The objective of this work has mainly been to contribute to the knowledge build-up required to allow the Swedish Armed Forces to create an effective information management and analysis process for the intelligence function of the Battle Group. Ever more areas of application have successively come within reach of database technology, while users' requirements for storage and access capacity, as well as reliability and economy of processing, have become easier to satisfy. The latter is mainly due to the exponential increase of the performance of computers and the concurrent reduction in their size and cost of acquisition. The choice of storage technology, whether it is based on ordinary files or on the far more advanced database concept, is often much less critical today than when database management systems were introduced around 1970. It is however not its capability of fast and efficient management of very large data sets that is the key advantage of database technology, but rather its much higher level of abstraction and far greater functionality compared to conventional application-controlled data processing and file management. Since the 1980's the relational model of data introduced by E. F. Codd has dominated business data management, but object-oriented and object-relational models have also been introduced, the latter category as a synthesis of the two first-mentioned. Object-oriented database management systems created a market niche for themselves during the 90's, predominantly in technological design applications for which relational databases lacked the functionality and structuring capacity that was required. A database management system must be able to handle very large sets of data. In many applications, capability to manage a large number of concurrent requests involving updates is a key requirement, so-called On-Line Transaction Processing (OLTP). In analysis and decision support applications, however, conventional techniques for database configuration can not be used, since they are unable to resolve all the issues that are characteristic of such applications, such as data selection, management of temporal and aggregated data and the controlled use of redundant storage. The use of so-called data warehouses has therefore become an important strategy to integrate heterogeneous data sources and to enable so-called On-Line Analytic Processing (OLAP).