Home > Articles

  • Print
  • + Share This
This chapter is from the book

Popular Data Mining Tools

A large number of software vendors provide powerful data mining tools. 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. 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). Noticeably but not surprisingly, the most popular data mining tools were originally developed by the well-established statistical software companies (SPSS, SAS, and StatSoft). 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.

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. 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.

In addition to the commercial data mining tools, there are several open source and/or free data mining software tools available over the Internet. 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/). Weka includes a large number of algorithms for different data mining tasks and has an intuitive user interface. Another quickly popularized free (for noncommercial use) data mining tool is RapidMiner, developed by RapidMiner.com (which can be downloaded from rapidminer.com). 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.

Another free and open source data mining tool with an appealing workflow-type graphical user interface is KNIME Analytics Platform (which can be downloaded from knime.org). A detailed description of KNIME can be found in Appendix A.

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. 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). With the cloud-based analytics, this deficiency of open source tools is no longer as prominent as it used to be. 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. 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. Table 2.1 lists the major data mining software products and their websites.

Table 2.1 Popular Data Mining Software Tools

Product

Website (URL)

KNIME Analytics Platform

knime.org

SAS Enterprise Miner

https://www.sas.com/en_us/software/enterprise-miner.html

IBM SPSS Modeler

ibm.com/products/spss-modeler

TIBCO Statistica

docs.tibco.com/products/tibco-statistica

RapidMiner

rapidminer.com

PolyAnalyst

megaputer.com/polyanalyst.php

Salford Predictive Modeler

salford-systems.com

XLMiner

https://www.solver.com/xlminer-platform

DataRobot Enterprise Analytics and AI

https://www.datarobot.com/

Databricks Unified Analytics Platform

https://databricks.com/

Apache Spark Analytics

https://spark.apache.org/

H2O Analytics

https://h2oanalytics.com/

Teradata Warehouse Miner

https://www.teradata.com/

Oracle Data Mining

oracle.com/database/technologies/advanced-analytics/odm.html

R for Analytics

https://www.r-project.org/

Python for Analytics

https://www.python.org/

Open Source Analytical API Platform for JavaScript

https://cube.dev/

Microsoft’s SQL Server includes a suite of business intelligence capabilities that has become increasingly popular for data mining studies. 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. 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). The consortium was established to enable universities around the world to access enterprise technology without having to maintain the necessary hardware and software on their own campuses. The consortium provides a wide range of business intelligence development tools (e.g., data mining, cube building, business reporting) as well as a number of large, realistic data sets from companies such as Sam’s Club, Dillard’s, and Tyson Foods. The Microsoft Enterprise Consortium is free of charge and can be used only for academic purposes. The Sam M. Walton College of Business at the University of Arkansas hosts the enterprise system and allows consortium members and their students to access these resources using a simple remote desktop connection. For details about becoming a part of the consortium and easy-to-follow tutorials and examples, see https://walton.uark.edu/enterprise/Microsoft/index.php.

In May 2019, KDnuggets (a well-known web portal for data mining and analytics links and resources) conducted its 20th annual software poll on the following question: “What analytics, data science, machine learning software/tools have you used in the last three years (2017–2019) for a real project?” This poll received huge attention from the analytics and data science community, attracting more than 1,800 unique voters. The poll measures both how widely a data analytics/data science software tool is used and how strongly the vendors advocate for their tool. Here are some of the interesting findings that came out of the poll:

  • Many business analytics and data science software users use more than one tool to carry out data analytics projects. According to the poll, the average number of tools used by a person or vendor was 6.1 in 2019 (compared to 3.7 in 2014). This is a clear indication that most data scientists use a combination of tools (commercial, free/open source software, programming languages, and open access algorithms and model libraries as community projects). Using only one tool or language seems to be insufficient to deal with the requirements of the new generation of analytics projects.

  • The popularity of free and open-source software tools and programming languages far exceeded that of the commercial tools. More than two-thirds of the most popular tools in the top 40 are either free/open source software with graphical user interfaces or programming languages and libraries of models/algorithms for data analytics. Overall, the most popular tool was Python (with 65% of the votes), as was the case in 2018.

  • While the percentage of votes for big data tools (e.g., Apache Spark, Hadoop, Kafka) and technologies decreased, the deep learning tools, technologies, and libraries (e.g., TensorFlow, Keras, PyTorch) gained significant popularity.

Figure 2.4 shows the results of the poll for tools that placed in the top 40, based on the number of unique votes they received. The chart in this figure shows the number of votes for each of these tools.

To reduce bias through multiple voting, in this poll, KDnuggets used email verification, which may potentially reduce the total number of votes but made the results less biased and more representative.

  • + Share This
  • 🔖 Save To Your Account

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020