Data Mining Tools

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Showing 1 - 20 of 34 products
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Showing 1 - 20 of 34 products

Hexomatic

Hexomatic is a no-code, work automation platform that enables businesses to harness the internet as their own data source and leverage ready-made automations to scale time-consuming tasks. This platform allows users to scrape the ...Read more

4.70 (20 reviews)

Alteryx Designer

Alteryx is the launchpad for automation breakthroughs. Be it your personal growth, achieving transformative digital outcomes, or rapid innovation, the results are unparalleled. The unique innovation that converges analytics, ...Read more

4.75 (77 reviews)

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Octoparse

Octoparse is a cloud-based web data extraction solution that helps users extract relevant information from various types of websites. It enables users from a variety of industries to scrape unstructured data and save it in differe...Read more

4.55 (60 reviews)

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Neural Designer

Neural Designer is an on-premise business intelligence (BI) and machine learning solution designed for any kind of business. With it, you can build artificial intelligence models using neural networks to discover relationships, re...Read more

4.90 (10 reviews)

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Periscope

Periscope Data is Business Intelligence software that allows users to keep data in one interactive dashboard. Functionalities include dashboards and scorecards, data warehousing, data mining and predictive analytics, ETL, OLAP, a ...Read more

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IntelliFront BI

IntelliFront BI by ChistianStevens Software allows businesses to view multiple data sets in one place. The system offers real-time dashboards with on-demand reporting. Users have access to business process automation, report sched...Read more

4.00 (5 reviews)

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Mozenda

With over 10 years of experience, Mozenda enables midsize software and IT companies to automate website data extraction from any website. The tool allows users to view, organize and run reports on data collected from websites. It ...Read more

4.38 (29 reviews)

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Centralpoint

Centralpoint, by Oxcyon is featured in Gartner’s Magic Quadrant for Digital Experience Platforms is a Microsoft based technology which be installed either on-premise or in the cloud. It is an N-Tiered, highly scalable, roles based...Read more

4.67 (6 reviews)

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RapidMiner

RapidMiner is a cloud-based and on-premise data science solution, which helps small to large organizations access, load and analyze structured and unstructured data. Key features include process automation, model validation, data ...Read more

4.43 (21 reviews)

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Zyte

From the creators of Scrapy, Scrapinghub is a data extraction solution that provides tailor-made data services to companies of any size as well as developer tools for web scraping - like proxy network, crawler management, javascri...Read more

4.47 (34 reviews)

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Software pricing tips

Read our Data Mining Tools Buyers Guide

Subscription models

  • Per employee/per month: This model allows you to pay a monthly fee for each of your employees.
  • Per user/per month: Users pay a monthly fee for users—normally administrative users—rather than all employees.

Perpetual license

  • This involves paying an upfront sum for the license to own the software and use it indefinitely.
  • This is the more traditional model and is most common with on-premise applications and with larger businesses.

Rated best value for money

Lucidworks Fusion

Lucidworks Fusion is a cloud-based solution designed to help IT teams manage data discovery through natural language processing (NLP), query intent classification, information clustering and ranking algorithms. Key features includ...Read more

4.00 (1 reviews)

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Statgraphics Centurion

Statgraphics is a business intelligence (BI) solution that helps enterprises utilize collected information to facilitate data visualization, modeling and predictive analysis. It provides professionals with interfaces for text mini...Read more

4.48 (31 reviews)

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Wolfram Mathematica

Wolfram Mathematica is a technical computing solution that provides businesses of all sizes with tools for image processing, data visualization and theoretic experiments. The notebook interface enables users to organize documents ...Read more

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JMP

JMP is an on-premise data analytics solution that helps scientists, engineers and data explorers understand complex data relationships and visualize them via interactive dashboards. The data acquisition and cleanup functionalities...Read more

4.62 (42 reviews)

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IOTICSpace

IOTICS IS SOFTWARE FOR DATA INTERACTIONS. WE ARE CHANGING HOW THE WORLD USES AND SHARES DATA. In IOTICSpace digital twins virtualize data sources and consumers. In a decentralised data mesh digital twins use semantic web technolo...Read more

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Diffbot

Diffbot is a cloud-based knowledge management solution designed for businesses of all sizes. It applies to various segments including marketing, business intelligence, sales and recruitment. The solution is primarily used by engin...Read more

4.50 (4 reviews)

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Grepsr

GREPSR EMPOWERS BUSINESSES WITH RELIABLE, ACCURATE AND ACTIONABLE WEB DATA. First, we'll discuss the specifics of your data needs and the KPIs you would like to have in order to ensure successful project execution. We will then...Read more

4.72 (46 reviews)

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Lex Machina

Lex Machina is a cloud-based solution designed to help law firms of all sizes streamline the entire litigation lifecycle, from processing raw records to organizing data using Lexpressions, a natural language processing (NLP) techn...Read more

0.00 (1 reviews)

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Planergy

Planergy (previously PurchaseControl) is a cloud-based solution that helps businesses streamline the entire procurement lifecycle, from managing purchasing to receiving. It enables users to generate order requests via forms with p...Read more

4.60 (10 reviews)

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SPSS

SPSS is a cloud-based data analysis engine that helps individuals and enterprises by providing statistical foresight to improve efficiency across the business. Designed for businesses of all sizes, it offers solutions including fr...Read more

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Popular Data Mining Tools Comparisons

Buyers Guide

Last Updated: March 11, 2022

 A major challenge for businesses is how to turn large, convoluted data sets into information that users can leverage to improve operations. Meanwhile, as companies struggle to find the best approach, their data sets continue growing larger and more convoluted, while some of their competitors turn their own analyses into actionable insight and competitive advantage.

Data mining software addresses this exact problem. It’s a core application in most business intelligence initiatives and it’s often the only tool able to extract insight from mountains of data. And as computing and application costs continue to become more affordable, data mining is no longer an exclusively enterprise-class endeavor. Now, even companies in the SMB space are rolling out data mining initiatives and reaping their rewards.

In this buyer’s guide, we address the following points and answer the following questions:

What Is Data Mining Software?
Common Features of Data Mining Software
Benefits of Data Mining
Key Considerations for Selecting Data Mining Software

What Is Data Mining Software?

Data mining software allows users to apply semi-automated and predictive analyses to parse raw data and find new ways to look at information. It’s typically applied to very large data sets, those with many variables or related functions, or any data set too large or complex for human analysis.

Some examples of how data mining is used in different industries include:

  • Ecommerce companies use data mining to analyze visitor demographics and discover how to deliver a better customer experience. They might, for example, find that some products sell better during certain times of the day. Using this insight they could increase sales by reconfiguring which products are displayed based on time of day.

  • Insurance companies use data mining to find patterns in populations that can inform the processes of underwriting and policy management. Armed with these insights, they can offer more attractive policies tailored to specific customer segments.

  • Service providers use data mining to better cater to their clients’ needs and make suggestions for the most effective upsell opportunities. Cable and internet service providers regularly mine customer data to improve their service offerings.

  • Governmental agencies use data mining to better understand many large-scale social, political and economic changes. A local government might, for example, discover better ways to develop its road and traffic infrastructure by mining the data created from the monitoring of traffic patterns throughout the week.

It’s also important to note what data mining software does not do. Namely, it doesn’t collect the data in the first place. Most data mining solutions are designed to work with pre-existing data sets. Buyers are advised to pay close attention to the language and descriptions used in vendor marketing materials to ensure the tool they buy is the actual solution they need.

Common Features of Data Mining Software

Data mining platforms often include a variety of tools, sometimes borrowing from other, related fields such as machine learning, artificial intelligence and statistical modeling. The offerings do vary from vendor to vendor, but there are some features common across the board. These can include:

Data pre-processing Help convert existing data-sets into the proper formats necessary in order to begin the mining process.
Cluster analysis These tools can categorize (or cluster) groups of entries based on predetermined variables, or can suggest variables which will yield the most distinct clustering.
Anomaly detection A common data mining tool that finds outliers and anomalous entries in vast, complex and/or interrelated data-sets.
Process automation Data mining, by definition, requires automation. But different data mining platforms require different degrees of human input and oversight.

Benefits of Data Mining

Data mining applications help users discover correlations and connections within large data sets. These often include numerous entries with multiple variables and can even contain mixed structured and unstructured data. Because of the size and complexity of these data sets, any valuable correlations within them would have gone unnoticed if not for the tireless algorithmic analysis performed with data mining software.

While specific goals vary from company to company, we can say that companies generally implement data mining systems to:

  • Accelerate discovery with semi-automated analyses

  • Segment customers into groups based on homogeneous activities and demographics 

  • Generate models to predict future trends


A classic example of how these systems can be used is with customer purchasing patterns at grocery stores. If shoppers tend to buy items such as toilet paper, diapers and alcohol before the weekend, retailers can place these items closer together to maximize revenue. Store owners can further capitalize on this opportunity by running specials on these items to encourage additional purchases.

Key Considerations for Selecting Data Mining Software

When evaluating data mining software, you should consider the following:

Best-of-breed or integrated suite? Buyers should consider whether they want a stand-alone, best-of-breed data mining application or would prefer to go with the data mining module from their existing Enterprise Resource Planning (ERP) provider. If buyers choose to evaluate stand-alone systems, they should discuss integration capabilities with these pure-play vendors.

Do you need to invest in hardware? Businesses without IT resources (or a budget to invest in new, faster servers) may choose to instead host their data in the cloud. However, in-memory processing advances have improved the speed and capability of these applications, lessening the IT investment previously necessary to effectively utilize data mining applications.

Do you have the talent to utilize these applications? Like with any software application, data mining solutions require the right questions to discover useful answers within data. For example, if you are evaluating data mining tools from enterprise vendor SAS, do you have analysts versed in the sample, explore, modify, model, assess (SEMMA) framework used in SAS data mining applications? Businesses must have sophisticated users to make the most out of their investment in these systems.