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Data mining software is a tool used to identify patterns in large sets of data. This area of computer software has expanded dramatically in the past few years as firms look for ways to translate large volumes of information into useful information for decision making. The ability to clearly identify cause and effect, patterns in human behavior, trends, and other metrics is central to proper management of any business. The benefits to data mining software are clear to most users, but how to obtain the desired information and exactly how the process works is poorly understood by the general business community.
There are three aspects to data mining software that describe the process: conversion of raw data, mining programming scripts, and interpretation. This process is also known as knowledge discovery in databases (KDD) and is used to describe all aspects of data mining, including the structure of the data, methods of accessing data, and the system architecture. There is a range of companies offering data mining software, and a solid understanding of the concepts that drive this product is essential to the successful and appropriate use of the technology.
The first requirement for using any data mining software is to convert the raw data into a target data set. For example, raw data is the database of all the sales processed within a broad time frame. A target data set has only data that meets a specific criterion. This may include transactions processed within a specific time frame. Included in the data set specifications are the individual fields that are included. This may include the date of the transaction, payment method, store location, product description, and number of items purchased.
Once the data set specifications are determined, then the data is cleaned to remove excess information, noise, or incomplete data files. This process typically requires the use of programming skills, data management techniques, and an overall understanding of the primary data concepts in place. A data mart or data warehouse is the most common tool used to store the data tables in a way that can be easily accessed by the data mining software program.
The actual data mining programming scripts can be customized, or programmers can utilize standard scripts included in the data mining software package. The vast majority of data mining software programs use regression analysis, fuzzy logic, and algorithms to identify specific patterns that meet user specifications. The interpretation of the results requires human intervention, time, and skills in statistics, pattern recognition, and related mathematical skills. It is important to remember that the program can only return options based on the specifications provided by the user. Poorly defined specifications and low data quality will have a negative impact on the validity of the results.