Data mining (also known as knowledge discovery) is the process of gathering large amounts of valid information, analyzing that information and condensing it into meaningful data. It brings together the fields of computer science, statistics and artificial intelligence.
Data mining is extremely important to the business community as it enables informed, knowledge-driven decisions to be taken. This is achieved by allowing institutions to visualise and understand their data, and to identify patterns and relationships that dictate business outcomes. Above all, data mining is recognised as an important tool for any business as it enables data to be converted into business intelligence. This intelligence can be used to generate accurate trends about customers’ purchasing behaviour, or to help in the assessment of customers’ credit rating. By embracing data mining technology, organisations can increase their revenue stream, help to minimise costs, as well as improving their competitive position. Data mining is also important in the fields of science and engineering, for surveillance, and in gaming (e.g. chess endgames).
There are dozens of different techniques that are used in data mining to examine and transform data. Some of the common techniques include decision trees, artificial neural networks, nearest neighbour method, generic algorithms, and rule induction.
This article focuses in selecting the best free software for performing data mining. Hopefully, there will be something of interest here for anyone who needs to make strategic decisions when confronted with large amounts of information.
So, let’s explore the 11 data mining tools at hand. For each application we have compiled its own portal page, providing a screenshot of the software in action, a full description with an in-depth analysis of its features, together with links to relevant resources.
|Data Mining Software|
|R||Software environment for statistical computing and graphics|
|RapidMiner||Knowledge discovery in databases, machine learning, and data mining|
|MOA||Software environment for data stream mining|
|Orange||Component-based framework for machine learning and data mining|
|ROOT||Aimed at solving the data analysis challenges of high-energy physics|
|Rattle||Gnome cross platform GUI for Data Mining using R|
|ELKI||Data mining software framework developed for use in research and teaching|
|DataMelt||Full-featured data-analysis framework for scientists, engineers and students|
|KNIME||Konstanz Information Miner|
|Weka||Waikato Environment for Knowledge Analysis|
|KEEL||Assess evolutionary algorithms for data mining|
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