IQ Intelligent Systems (IQS) are system within a system that attempts to analyze data and seek consistency or pattern within data. This system does this by matching the output of a system with known facts and rules.

The first step in IQS is data abstraction. Typically, data is abstracted by a process called domain verification. From the term “data abstraction,” it can be said that the system separates the input from the input to achieve some goal. The separation may be between normal data and potential data. It can also be between past data and the current data. Whatever the type is, the system must produce a consistent result. To do so, the system may have to be programmed in its calculation.

The second step in IQS is to find the patterns in the data. One way to accomplish this is to apply statistics or some other logical analysis. Another way is to examine common patterns. For example, if you have a sales force that typically sells products that are blue in color, you can analyze your sales data by looking for the classes of products that are consistently sold in blue stores. Then you can target your efforts to those blue-selling products.

The third step is to create templates. These templates can be template data-ctors or they can be mappings from one domain or function to another. For example, if you have a customer that calls you and you provide him with a product that is blue in color, you can map this event to a template of blue products or to a HOT100 item. That is one example of a mapping from one domain to another.

There are many benefits to using IQS, but these are just a few. IQS programs are a very powerful tool that can help you analyze data in much more effective ways than you ever imagined. You just need to remember that the brighter the data, the more powerful the analysis can be.