The 8 Best Data Mining Tools and Software to Consider for 2022

The Best Data Mining Tools and Software

Solutions Review’s listing of the best data mining tools and software is an annual mashup of products that best represent current market conditions, according to the crowd. Our editors selected the best data mining tools and software based on each solution’s Authority Score; a meta-analysis of real user sentiment through the web’s most trusted business software review sites and our own proprietary five-point inclusion criteria.

The editors at Solutions Review have developed this resource to assist buyers in search of the best data mining tools and software to fit the needs of their organization. Choosing the right vendor and solution can be a complicated process — one that requires in-depth research and often comes down to more than just the solution and its technical capabilities. To make your search a little easier, we’ve profiled the best data mining tools and software providers all in one place. We’ve also included platform and product line names and introductory software tutorials straight from the source so you can see each solution in action.

Note: The best data mining tools and software are listed in alphabetical order.

The Best Data Mining Tools and Software

Altair

Platform: Altair Data Analytics

Related products: Altair Knowledge Studio, Altair Altair SmartWorks, Altair Analytics Workbench, Altair Analytics Compiler

Description: Altair offers a suite of machine learning and AI solutions through its data analytics portfolio. Designed for people with different skill sets, the portfolio delivers transparency and automation with features such as AutoML and Explainable AI and streamlines model building so more time can be spent analyzing and results can be trusted. The flexible no-code approach doesn’t restrict how models are configured and tuned, giving users control over model building. With support for common SAS language, R, Python and engines, users can integrate new models built using Altair into existing analytics infrastructure.

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

Alteryx

Platform: Alteryx Analytics Process Automation

Related products: Alteryx Designer, Alteryx Intelligence Suite, Alteryx Server, Alteryx Connect, Alteryx Promote

Description: Alteryx offers data science and machine learning functionality via a suite of software products. Headlined by Alteryx Designer which automates data preparation, data blending, reporting, predictive analytics, and data science, the self-service platform touts more than 260 drag-and-drop building blocks. Alteryx lets users see variable relationships and distributions quickly, as well as select and compare algorithm performance with ease. No coding is required while the software can be deployed in the cloud, behind your own firewall, or in a hosted environment. 

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

Dataiku

Dataiku 150

Platform: Dataiku Data Science Studio (DSS)

Description: Dataiku offers an advanced analytics solution that allows organizations to create their own data tools. The company’s flagship product features a team-based user interface for both data analysts and data scientists. Dataiku’s unified framework for development and deployment provides immediate access to all the features needed to design data tools from scratch. Users can then apply machine learning and data science techniques to build and deploy predictive data flows. 

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

KNIME

KNIME Logo

Platform: KNIME Analytics Platform

Related products: KNIME Server

Description: KNIME Analytics is an open-source platform for creating data science. It enables the creation of visual workflows via a drag-and-drop-style graphical interface that requires no coding. Users can choose from more than 2000 nodes to build workflows, model each step of analysis, control the flow of data, and ensure work is current. KNIME can blend data from any source and shape data to derive statistics, clean data, and extract and select features. The product leverages AI and machine learning and can visualize data with classic and advanced charts. 

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

Microsoft

Platform: Azure Machine Learning

Related products: Azure Data Factory, Azure Data Catalog, Azure HDInsight, Azure Databricks, Azure DevOps, Power BI

Description: The Azure Machine Learning service lets developers and data scientists build, train, and deploy machine learning models. The product features productivity for all skill levels via a code-first and drag-and-drop designer, and automated machine learning. It also features expansive MLops capabilities that integrate with existing DevOps processes. The service touts responsible machine learning so users can understand models with interpretability and fairness, as well as protect data with differential privacy and confidential computing. Azure Machine Learning supports open-source frameworks and languages like MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R. 

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

RapidMiner

Platform: RapidMiner Studio

Related products: RapidMiner AI Hub, RapidMiner Go, RapidMiner Notebooks, RapidMiner AI Cloud

Description: RapidMiner offers a data science platform that enables people of all skill levels across the enterprise to build and operate AI solutions. The product covers the full lifecycle of the AI production process, from data exploration and data preparation to model building, model deployment, and model operations. RapidMiner provides the depth that data scientists needbut simplifies AI for everyone else via a visual user interface that streamlines the process of building and understanding complex models.

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

SAS

Platform: SAS Visual Data Mining and Machine Learning

Related products: SAS Viya, SAS Visual Machine Learning, SAS Visual Data Science, SAS Data Science Programming, SAS Visual Data Decisioning

Description: SAS offers a suite of advanced analytics and data science products which is headlined by SASVisual Data Mining and Machine Learning. The product provides access to data in any format and from any source, as well as automated data preparation and data lineage and model management. SAS Visual Data Mining and Machine Learning automatically generates insights for common variables across models. It also features natural language generation for creating project summaries. The companion SAS Model Manager enables users to register SAS and open-source models within projects or as standalone models.

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.

TIBCO

Platform: TIBCO Data Science

Related products: TIBCO Spotfire, TIBCO Streaming

Description: TIBCO offers an expansive product portfolio for modern BI, descriptive and predictive analytics, and streaming analytics and data science. TIBCO Data Science lets users do data preparation, model building, deployment and monitoring. It also features AutoML, drag-and-drop workflows, and embedded Jupyter Notebooks for sharing reusable modules. Users can run workflows on TIBCO’s Spotfire Analytics and leverage TensorFlow, SageMaker, Rekognition and Cognitive Services to orchestrate open source.

Learn more and compare products with the Solutions Review Buyer’s Guide for Data Science and Machine Learning Platforms.
Timothy King
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