Business Intelligence Buyer's Guide

Data Science and Machine Learning Solutions Directory

Below is a directory of Data Science and Machine Learning platforms, vendors, tools and software solutions including a company overview, links to social media and contact information for the top providers. If you would like a printed version of this page including complete solutions profiles and a list of the top questions to ask in an RFP – Request for Proposal, click here for a Free PDF.

Solutions Overview

Altair (formerly Datawatch) offers a suite of solutions through its Knowledge Works portfolio and is headlined by an advanced data mining and predictive analytics workbench called Knowledge Studio. The product features pa...

Altair (formerly Datawatch) offers a suite of solutions through its Knowledge Works portfolio and is headlined by an advanced data mining and predictive analytics workbench called Knowledge Studio. The product features patented Decision Trees, Strategy Trees, and a workflow and wizard-driven graphical user interface. It also includes capabilities for data preparation tasks, visual data profiling, advanced predictive modeling, and in-database analytics. Users can import and export using common languages like R and Python, as well as data types like SAS, RDBMS, CSV, Excel, and SPSS.

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Altair Knowledge Works is made up of Altair Knowledge Studio, Altair Knowledge Seeker (data visualization, segmentation, and strategy development), and Altair Knowledge Studio for Apache Spark. The solution provider is known for offering an easy-to-use platform for technical and non-technical users. Altair also touts strong features for augmented data preparation through integration with its advanced data preparation tools Altair Monarch and Altair Knowledge Hub. The provider updated its entire line of analytics products in mid-2020.

Solutions Overview

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 sci...

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.

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Alteryx offers simple connection to data sources while in-database analytic building blocks utilize the cloud to run analytics against big data sources. Integrated data preparation and data quality during model creation is a major value-add. Alteryx is unique due to its speed text mining and natural language processing, and the ability to enrich insights with location intelligence. The vendor’s no-code approach is a major consideration for organizations that need tools for distinct user personas as well. Alteryx made several high-profile feature updates across its analytic product line in 2020.

Solutions Overview

Anaconda offers its data science and machine learning capabilities via a number of different product editions. Its flagship product is Anaconda Enterprise, an open-source Python and R-focused platform. The tool enables yo...

Anaconda offers its data science and machine learning capabilities via a number of different product editions. Its flagship product is Anaconda Enterprise, an open-source Python and R-focused platform. The tool enables you to perform data science and machine learning on Linux, Windows, and Mac OS. Anaconda allows users to download more than 1,500 Python and R data science packages, manage libraries, dependencies, and environments, and analyze data with Dask, NumPy, pandas, and Numba. You can then visualize results generated in Anaconda with Matplotlib, Bokeh, Datashader, and Holoviews.

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Anaconda’s product line includes Anaconda Individual Edition (open-source distribution), Commercial Edition (Commercial Package Manager), Team Edition (Package Repository) and the Enterprise option. Anaconda is popular among coders and in the financial services, energy, healthcare, manufacturing and retail industries. The product provides access to all R and Python libraries as well, and the ability to use Hadoop, Hadoop YARN and Kubernetes clusters are major value-adds.

Solutions Overview

Databricks offers a cloud and Apache Spark-based unified analytics platform that combines data engineering and data science functionality. The product leverages an array of open-source languages, and includes proprietary ...

Databricks offers a cloud and Apache Spark-based unified analytics platform that combines data engineering and data science functionality. The product leverages an array of open-source languages, and includes proprietary features for operationalization, performance, and real-time enablement on Amazon Web Services. A Data Science Workspace enables users to explore data and build models collaboratively. It also provides one-click access to preconfigured ML environments for augmented machine learning with popular frameworks.

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Databricks is a leading voice in the Apache Spark community and serves customers in a variety of industries. Its unified platform offers spans capabilities from data lake and ETL to machine learning and an enterprise cloud service. Recent enhancements include SQL Analytics, a cloud data warehouse that integrates with BI tools and enables users to query recent data in data lakes. Databricks raised $1 billion in pre-IPO funding in February to move ahead with product innovations and scale support for its new lakehouse data architecture.

Solutions Overview

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. Datai...

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.

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Dataiku is unique in that houses all data science and machine learning functionality in a single platform. Users enjoy the product’s ease of use and operation, as well as features for enabling collaboration across teams. The Dataiku 7 update (released in March 2020) was highlighted by deeper integrations for technical professionals who work on machine learning project development. There is also new row-level explainability for white-box AI and Kubernetes-powered web apps that extend the product. Dataiku raised $100 million in Series D funding in August.

Solutions Overview

DataRobot offers an enterprise AI platform that automates the end-to-end process for building, deploying, and maintaining AI. The product is powered by open-source algorithms and can be leveraged on-prem, in the cloud or ...

DataRobot offers an enterprise AI platform that automates the end-to-end process for building, deploying, and maintaining AI. The product is powered by open-source algorithms and can be leveraged on-prem, in the cloud or as a fully-managed AI services. DataRobot includes several independent but fully integrated tools (Paxata Data Preparation, Automated Machine Learning, Automated Time Series, MLOps, and AI applications), and each can be deployed in multiple ways to match business needs and IT requirements.

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DataRobot’s augmented data science platform can be leveraged by all user types, from AI creators like data scientists, data engineers, software developers, and business analysts, to AI operators in DevOps and IT, as well as AI consumers within lines of business. Additional product highlights include Visual AI for working with images just like any other data type, a trusted AI framework that incorporates best practices and recent research developments, and feature discovery. DataRobot can be deployed as managed, private, hybrid or on-prem.

Solutions Overview

Domino Data Lab offers an enterprise data science platform that allows data scientists to build and run predictive models. The product helps organizations with the development and delivery of these models via infrastructu...

Domino Data Lab offers an enterprise data science platform that allows data scientists to build and run predictive models. The product helps organizations with the development and delivery of these models via infrastructure automation and collaboration. Domino provides users access to a data science Workbench that provides open source and commercial tools for batch experiments, as well as Model Delivery so they can publish APIs and web apps or schedule reports. The company has raised more than $120 million in funding since its founding in 2013.

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The Domino Data Science Platform features an open architecture that is excellent for collaboration. The Workbench component lets users utilize the tools they want and run computationally intensive experiments simultaneously. Domino is also unique through its results and progress tracking capabilities which lets you find and reproduce past results, avoid inconsistent versions, and link Domino projects to a Jira ticket. Domino Model Monitor is available as an add-on to track data drift, prediction quality, and analyze failure conditions.

Solutions Overview

Google Cloud AI offers one of the largest machine learning stacks in the space and offers an expanding list of products for a variety of use cases. The product is fully managed and offers excellent governance with interpr...

Google Cloud AI offers one of the largest machine learning stacks in the space and offers an expanding list of products for a variety of use cases. The product is fully managed and offers excellent governance with interpretable models. Key features include a built-in Data Labeling Service, AutoML, model validation via AI Explanations, a What-If Tool which helps you understand model outputs, cloud model deployment with Prediction, and MLOps via the Pipeline tool.

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The Google Cloud AI platform touts an expansive set of tools including Google Cloud Data Fusion, Cloud AutoML, BigQuery ML, AI Platform Notebooks and TensorFlow. The technology mega-vendor is set to launch a unified offering with AutoML tables, XAI, AI platform pipelines and more in 2021. Google’s data science and machine learning capabilities are impressive and growing, and an entrenched user base have it on pace to become a major player in the spacer in short order.

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Solutions Overview

H2O.ai offers a number of AI and data science products, headlined by its commercial platform H2O Driverless AI. Driverless AI is a fully open-source, distributed in-memory machine learning platform with linear scalability...

H2O.ai offers a number of AI and data science products, headlined by its commercial platform H2O Driverless AI. Driverless AI is a fully open-source, distributed in-memory machine learning platform with linear scalability. H2O supports widely used statistical and machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O has also developed AutoML functionality that automatically runs through all the algorithms to produce a leaderboard of the best models.

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The H2O.ai Driverless AI platform is buoyed by add-on modules in MLOps and AutoDoc. The company also offers a collection of open-source tools with commercial support options like the H2O 3 platform, AutoML for ML, Sparkling Water for Spark integration, and Wave for application development. The Bring-Your-Own-Recipes feature is a major value-add to working with this provider. End-user segment is positive surrounding all of the automation that H2O includes in its products as well.

Solutions Overview

IBM Watson Studio enables users to build, run, and manage AI models at scale across any cloud. The product is a part of IBM Cloud Pak for Data, the company’s main data and AI platform. The solution lets you automate AI li...

IBM Watson Studio enables users to build, run, and manage AI models at scale across any cloud. The product is a part of IBM Cloud Pak for Data, the company’s main data and AI platform. The solution lets you automate AI lifecycle management, govern and secure open-source notebooks, prepare and build models visually, deploy and run models through one-click integration, and manage and monitor models with explainable AI. IBM Watson Studio offers a flexible architecture that allows users to utilize open-source frameworks like PyTorch, TensorFlow, and scikit-learn.

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IBM Watson Studio’s visual workflow interface (graphic canvas) make it well suited to serve a number of different user personas. The technology mega-vendor also pays special attention to responsible and explainable AI and governance. Additional capabilities of note include data preparation, simplified modeling with the SPSS Modeler, the ability to monitor quality, fairness and drift metrics, and examining key model metrics via a side-by-side comparison.

Solutions Overview

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...

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.

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KNIME offers an advanced platform with deep data science and machine learning capabilities. It touts nearly 4,000 nodes for connecting to different data types and sources and can solve for virtually all of the major use cases in enterprise settings. KNIME’s open-source nature is a major strength of the product and lets customers explore different components at will. KNIME unveiled Integrated Deployment in April, a new approach aimed at eliminating the gap between the creation of models and their use in production.

Solutions Overview

MathWorks MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating ...

MathWorks MATLAB combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, tested, and fully documented. MATLAB apps let you see how different algorithms work with your data as well.

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MathWorks is best for large use cases with real-world applications. The vendor offers an impressive collection of AI features, and verifiable machine learning is a major strength of the platform. In addition to MATLAB, MathWorks also offers its Simulink product for designing and simulating systems before moving to hardware. Simulink lets you explore and implement designs that you may not otherwise consider without having to write C, C++, or HDL code.

Solutions Overview

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, ...

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.

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While Microsoft’s data science and machine learning portfolio is expansive and well-suited to meet the needs of enterprise organizations, multipersona support is actually a strength of the product. Microsoft offers a number of related components in addition to Azure Machine Learning, including Azure Data Factory (cloud ETL), Azure Data Catalog, Azure HDInsight (managed cluster service for open-source analytics), Azure Databricks, Azure DevOps, and Power BI, the company’s flagship business intelligence and data analytics toolset.

Solutions Overview

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 expl...

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 need but simplifies AI for everyone else via a visual user interface that streamlines the process of building and understanding complex models.

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RapidMiner is a consideration for organizations seeking to utilize AI and machine learning to support and automate business decisions. The extensibility of an open-source core helps ensure that RapidMiner can be used to support nearly any use case, and a shallow learning curve makes it easy for anyone to build and deploy effective models. Those in the manufacturing vertical may find RapidMiner particularly interesting considering the considerable adoption of AI by organizations in that space.

Solutions Overview

SAS offers a suite of advanced analytics and data science products which is headlined by SAS Visual Data Mining and Machine Learning. The product provides access to data in any format and from any source, as well as autom...

SAS offers a suite of advanced analytics and data science products which is headlined by SAS Visual 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.

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SAS Visual Data Mining and Machine Learning is offered as a part of the SS Viya product line, which also includes SAS Visual Machine Learning, SAS Visual Data Science, SAS Data Science Programming, and SAS Visual Data Decisioning. SAS is unique due to its cloud-native architecture and the ability to utilize Viya functionality in a container-based setting. The company also touts integrations with an array of open-source tools and languages for a variety of use cases.

Solutions Overview

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 ...

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.

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TIBCO’s Connected Intelligence approach is the result of integrating together a number of different data analytics products, whether developed or acquired. In addition to TIBCO Data Science, the company also offers business intelligence and analytics functionality through TIBCO Spotfire and TIBCO Streaming. TIBCO is a top consideration for organizations that deploy data and analytics across a range of functions. The company most recently released new analytics features in September 2020. TIBCO acquired Information Builders in early 2021.