What Is a Data Mining Agent?

A data mining agent is a pseudo-intelligent computer program designed to ferret out specific types of data, along with identifying patterns among those data types. These agents are typically used to detect trends in data, alerting organizations to paradigm shifts so effective strategies can be implemented to either take advantage of or minimize the damage from alterations in trends. In addition to reading patterns, data mining agents can also "pull" or "retrieve" relevant data from databases, alerting end-users to the presence of selected information.

Conceptualize a data mining agent as a very limited type of virtual employee. In effect, this agent is nothing more than an employee tasked with sorting through employee records to perform one or more very specific jobs. For example, the agent could be programmed to monitor stock prices for a specific range of companies, throwing up a red flag if it notices any substantial deviations from historical trends. These agents are a bit like a smoke alarm; they only throw up signals if something is actually happening in the system.

In this way, a data mining agent acts to save valuable employee time, as it is no longer necessary to assign these elementary monitoring roles to specific employees. This frees up man hours in the organization, allowing employees to divert their attention elsewhere until the data mining agents alert them that something in the system is actually worth observing. Without the use of these agents, individual employees would have to observe and record changes in the surveyed systems on a daily basis.

Additionally, data mining agents can be used to sift through database records, retrieving specific requested information that would otherwise prove tedious or difficult for a human to retrieve. For example, a data mining agent can easily and tirelessly sift through millions of records to find something as tedious as "All sales exceeding 50 dollars from January 1st, 2001 to March 25th, 2009." Whereas a human could become tired and make mistakes during a particularly long and boring search, an agent will never fail to retrieve its stated objective.

Although useful, data mining agents have their limitations. With the current state of artificial intelligence technology, it is difficult for a data mining device to detect hidden or complex patterns more effectively than a skilled human. Thus, while these agents have their place in rote or constricted observations with specifically defined parameters, they are not as suitable for highly detailed patterns or those necessitating a touch of human intuition.