Analytical software applications now serve to support the analysis function by providing tools that permit the analyst to convert information into a variety of formats, from multiple sources, into graphic products that lead to greater understanding of the information by both the analyst and the ultimate user of analytical products. This is the part of the intelligence process that is typically referred to as data integration. Significant advances have been made in the development and improvement of these systems; further enhancements can be made through the application of cognitive ergonomics, specifically through the application of our knowledge about the critical thinking skills that must be supported.

Analysts can uncover and interpret relationships and patterns hidden in data through the generation of intuitive charts. Moreover, information about each entity and link portrayed on a chart can be accessed through embedded data cards connected to the displayed icons or through links from icons back to the database. A sample chart is shown below in Figure 3. The mechanics for obtaining the additional information is typically just a matter of clicking on the icon of interest.

One valuable capability that can be provided by analytical software applications is data filtering. An important critical thinking strategy to counter the effects of complexity is that of determining specific analytic objectives and filtering out information in the database that is not relevant to meeting that objective. Examples of specific analytical objectives include the following: defining the flow of money into a specific organization; clarifying the span of control of a specific individual; including only information above a specified level of validity; tracking events that occurred only during a specified time period; and examining financial transactions above a specified amount during a specified time period.

The results from pursuing these specific objectives might provide support to a set of premises that lead to the development of an inference about the who, what, when, where, why and how of the activity of interest. Other capabilities provided by analytical software include the following:

  • Switch between network and timeline views to identify patterns in both time and space.
  • Automatically compare labels, types, attributes, names and aliases when combining data from different sources.
  • Augment charts by including visuals such as maps and photographs.


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