Information Technology Reference
In-Depth Information
In cyberspace, the transformation of collected data into knowledge is a complex
process strongly dependent on the capability of analysis and on the availability of
technological tools. In the last few years, new technological tools have been developed to
fulfil the requirements of data collection, transformation, validation, storage, handling
and analysis in order to help decision-makers gain competitive advantage. These
requirements and constraints are common to the majority of human activities, from
enterprises or business management to information warfare and counterterrorism.
It is probably a more common occurrence than anyone would like to admit but the
events of September 11 have dramatically confirmed that, in heavy workload conditions,
intelligence analysts:
x Lose the ability to gain a deep insight into analysed data and the ability to process
this data into useful information for generating clear reports and persuasive
conclusions
x Fail to aggregate items of intelligence information or global pieces of evidence
that, taken as a whole, would suggest realistic hypotheses and forecasts that
should be taken very seriously
x Tend to filter out, for synthesis purposes, too much data and thereby generate
“thin” reports open to hierarchical changes and knowledge reduction on their way
to the final authority
The experience gained in the business environment might be a useful starting point for
a solution to intelligence problems.
2.
BUSINESS INTELLIGENCE: HISTORICAL SURVEY
2.1
Transactional systems
In the last decade, enterprises have sustained considerable expense collecting data
relevant to their business and building related databases aimed at accumulating a massive
amount of operational data (data that runs the daily transactions of enterprises).
Nevertheless, analysts, managers and decision-makers experience several problems in
directly accessing operational data and turning it into information needed for timely
decisions:
x They might not have the technical skill to use languages for data manipulation
and application programmes to query operational databases available either
within or outside the organization
x Related databases may have different architectures and, quite often, operational
data is not in the best format for the use envisaged by analysts
x The access to data and rigid customized query/reports requires prior preparation
by application developers and database administrators
x The technical burden posed on the analysts might distract them from their train of
thought
While these systems have significantly improved the automation and organization of
data, they offer minimal access and poor analytical capabilities. Thus, data warehouses
were developed to meet these requirements.
Search WWH ::
Custom Search