![]() The Microsoft Enterprise Consortium serves as the worldwide source for access to Microsoft’s SQL Server software suite for academic purposes (i.e., teaching and research). With SQL Server, data and analytic models are hosted in the same relational database environment, significantly increasing the efficiency of model execution while making model management a considerably easier task. Microsoft’s SQL Server includes a suite of business intelligence capabilities that has become increasingly popular for data mining studies. Open Source Analytical API Platform for JavaScript database/technologies/advanced-analytics/odm.html Table 2.1 Popular Data Mining Software Tools Table 2.1 lists the major data mining software products and their websites. ![]() In addition to software tools, code-based analytics tools and high-level programming languages (i.e., Python, R, JavaScript) are also gaining tremendous popularity in the world of analytics and data science. For instance, an analytics model can be developed with a small data sample in KNIME Analytics Platform and then deployed and executed on the cloud platform with the complete/large dataset. With the cloud-based analytics, this deficiency of open source tools is no longer as prominent as it used to be. The same data mining task involving a large data set may take a lot longer to complete with free software, and for some algorithms, it may not even complete (i.e., it may crash due to inefficient use of computer memory). The main difference between commercial tools, such as Enterprise Miner, IBM SPSS Modeler, and Statistica, and free tools, such as Weka, RapidMiner, and KNIME, is often the computational efficiency. A detailed description of KNIME can be found in Appendix A. Its graphically enhanced user interface, use of a rather large number of algorithms, and incorporation of a variety of data visualization features set it apart from the rest of the other free data mining tools.Īnother free and open source data mining tool with an appealing workflow-type graphical user interface is KNIME Analytics Platform (which can be downloaded from ). Another quickly popularized free (for noncommercial use) data mining tool is RapidMiner, developed by (which can be downloaded from ). Weka includes a large number of algorithms for different data mining tasks and has an intuitive user interface. Historically, the most popular free (and open source) data mining tool is Weka, which was is developed by several researchers from the University of Waikato in New Zealand (and can be downloaded from cs.waikato.ac.nz/ml/weka/). In addition to the commercial data mining tools, there are several open source and/or free data mining software tools available over the Internet. These BI tools are still primarily focused on descriptive analytics in the sense of multidimensional modeling and data visualization and are not considered to be direct competitors of the data mining tool vendors. Most of the business intelligence (BI) tool vendors (e.g., IBM Cognos, Oracle Hyperion, SAP Business Objects, Microstrategy, Teradata, Microsoft) also have some level of data mining capabilities integrated into their software offerings. ![]() This is largely because statistics is the foundation of data mining, and these companies have the means to cost-effectively develop them into full-scale data mining systems. Noticeably but not surprisingly, the most popular data mining tools were originally developed by the well-established statistical software companies (SPSS, SAS, and StatSoft). ![]() Examples of the vendors that provide data mining tools include IBM (IBM SPSS Modeler, formerly known as SPSS PASW Modeler and Clementine), SAS (Enterprise Miner), StatSoft (Statistica Data Miner-now a TIBCO company), KXEN (Infinite Insight-now a SAP company), Salford (CART, MARS, TreeNet, and RandomForest), Angoss (KnowledgeSTUDIO and KnowledgeSeeker), and Megaputer (PolyAnalyst). Some of these vendors are providers of only data mining and statistical analysis software, while others are large firms that provide wide ranges of software and hardware, along with consulting, in addition to data mining software products. Learn More Buy Popular Data Mining ToolsĪ large number of software vendors provide powerful data mining tools. Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, 2nd Edition, 2nd Edition
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