Finding software can be overwhelming. Software Advice has helped thousands of businesses choose the right data mining software so they can mine textual data and extract insights.

Showing 1-20 of 215 products

Domo

Domo is the Business Cloud®, empowering organizations of all sizes with BI leverage at cloud scale in record time. With Domo, BI-critical processes that took weeks, months or more can now be done on the fly, in minutes or seconds,... Read more

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Recent recommendations: 28 recommendations

Platforms: MacWinLinux
Deployments: Cloud
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ClicData

ClicData is a business intelligence (BI) dashboard solution designed for use primarily by small and midsized businesses. The tool enables end users to create reports and dashboards. A drag-and-drop interface designed for ease of use... Read more

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Recent recommendations: 16 recommendations

Platforms: MacWinLinux
Deployments: Cloud
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Sisense

SiSense offers a full suite of BI applications, as well as standalone data and text mining with innovative analytics tools that can be used by any type of user. A great solution to manage and support your business data. Read more

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Recent recommendations: 15 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Dundas BI

Dundas BI, from Dundas Data Visualization, is a browser-based business intelligence and data visualization platform that includes integrated dashboards, reporting tools, and data analytics. It provides end users the ability to create... Read more

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Recent recommendations: 15 recommendations

Platforms: MacWinLinux
Deployments: On premise
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Looker

Looker is a cloud-based business intelligence (BI) platform designed to explore and analyze data. The solution helps businesses to capture and analyze data from multiple sources and make data-driven decisions. Looker provides business... Read more

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Recent recommendations: 13 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Birst

Birst, an Infor Company, is a web-based networked BI and analytics solution that connects insights from various teams and helps in making informed decisions. The tool enables decentralized users to augment the enterprise data model... Read more

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Recent recommendations: 12 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Style Intelligence

InetSoft Style Intelligence is a business intelligence software platform that allows users to create dashboards, visual analyses and reports via a data mashup engine—a tool that integrates data in real time from multiple sources.... Read more

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Recent recommendations: 11 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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TARGIT Decision Suite

TARGIT is a fully-integrated business intelligence suite that can be deployed on-premise or in the Cloud. Functionality includes dashboards, ETL tools, data warehousing, predictive analysis, OLAP and ad hoc reporting. Read more

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Recent recommendations: 9 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Yellowfin

Yellowfin, a business intelligence platform, is a single integrated solution developed for companies across varying industries and scaling sizes. This system is customizable to suit businesses in accounting, advertising, agriculture,... Read more

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Recent recommendations: 5 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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BOARD

Created to combine business intelligence, corporate performance management, and business analytics, BOARD is a full-featured business intelligence system that serves midsize and enterprise-level companies in a variety of different... Read more

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Recent recommendations: 3 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Exago

Exago BI is a 100% web-based, end-to-end business analytics solution that’s designed to be embedded in web-based applications. Embedding Exago BI allows SaaS companies of all sizes to provide their customers with self-service ad... Read more

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Recent recommendations: 3 recommendations

Platforms: MacWinLinux
Deployments: CloudOn premise
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Lumenore

Lumenore is a cloud-based technology performance management platform that integrates with multiple data sources, including spreadsheets, databases, social media and any existing cloud-based or on-premise software solution. It is suitable... Read more

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Recent recommendations: 3 recommendations

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Deployments: Cloud
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dashboardMD

dashboardMD is a turnkey, cloud-based, enterprise data warehouse, and business intelligence solution that provides organizations in the healthcare industry with daily dashboards and reporting tools to measure clinical, financial and... Read more

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Recent recommendations: 2 recommendations

Platforms: MacWinLinux
Deployments: Cloud
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Phocas Business Intelligence

Phocas is a cloud-based, SaaS company specializing in data analytics for manufacturing, distribution and retail industries. Phocas uses sector knowledge to consolidate essential business data from common ERP, CRM and AP/AR systems... Read more

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Recent recommendations: 1 recommendations

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Deployments: CloudOn premise
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AtScale

AtScale is a data warehouse virtualization solution that creates a live connection between people and data without moving it, regardless of where it is stored or how it is formatted - on-premise or in the cloud - turning your data... Read more

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Recent recommendations: 1 recommendations

Platforms: MacWinLinux
Deployments: On premise
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Stratum

Stratum by Silvon is a robust business intelligence solution that was designed to meet the unique needs of business professionals working for manufacturing and distribution companies. Stratum offers a full suite of integrated analytic... Read more

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Deployments: CloudOn premise
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Ambition

Ambition is a cloud-based business intelligence (BI) solution that provides tools and functionalities that help businesses drive employee performance and manage sales operations. Key features include data transformation, private cloud... Read more

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Toucan Toco

Toucan Toco is a cloud-based data visualization solution designed to deliver data and insights to non-technical decision makers using visual data storytelling. With Toucan's application studio, businesses are able to create and display... Read more

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TrenData

TrenData People Analytics is a cloud-based business intelligence (BI) solution designed for midsize businesses across various industries. The solution offers various HR analytics and workforce management features such as compensation... Read more

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Dploy Solutions

Dploy Solutions is a cloud-based manufacturing and industrial IIoT software that helps businesses collect, combine and analyze performance data across plant floors and other operations departments. It allows users to gain real-time... Read more

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Buyers guide


Last Updated: February 14, 2020

 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
Recent Events

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.

Recent Events

Microsoft acquires LinkedIn. June, 2016: Microsoft corporation announced it had reached a deal to acquire the professional networking site LinkedIn for $26.2B. It’s generally agreed that the software giant is making the acquisition in large part to improve its data mining capabilities with LinkedIn’s vast stores of user data.

Data mining gives researchers insight into human behaviors. June, 2016: Researchers at Harvard University, Cornell University and Microsoft Corporation announce results of a study that looks at the factors that influence how people make decisions when under pressure.

Some consumers more open to data mining. June, 2016: As data mining becomes more familiar to consumers, it’s becoming clear that some are more willing to have their data mined than others.