{"id":4373,"date":"2019-02-06T13:25:24","date_gmt":"2019-02-06T18:25:24","guid":{"rendered":"https:\/\/solutionsreview.com\/business-intelligence\/?p=4373"},"modified":"2019-08-15T10:15:22","modified_gmt":"2019-08-15T14:15:22","slug":"the-4-major-players-in-data-science-and-machine-learning-platforms-2019","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/business-intelligence\/the-4-major-players-in-data-science-and-machine-learning-platforms-2019\/","title":{"rendered":"The 4 Major Players in Data Science and Machine Learning Platforms, 2019"},"content":{"rendered":"

\"The<\/p>\n

Data science and machine learning platforms come in a variety of shapes and sizes to meet the ever-changing needs of organizations and their increasingly complex big data environments. Businesses require data solutions that can serve any number of different use cases, and in the case of data science, can range from predictive analytics to natural language processing. There are both small and large providers that offer software to help these companies with both niche and common challenges, though choosing the vendor(s) that are right for your specific environment can be a daunting task.<\/p>\n

The following providers have recently been named leaders in the 2019 Gartner Magic Quadrant for Data Science and Machine Learning Platforms<\/em><\/a>. The report, which highlights and scores the top products in the industry, features these four tools as being cornerstones in the space. Each provider’s market share and product portfolios differ, which is what makes them interesting to the wider audience of data consumers. Niche and emerging vendors can only hope to replicate the kind of market presence that these providers have earned over a sustained period of time. Here we provide a brief blurb about each and links to product details so you can learn more.<\/p>\n

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\"RapidMiner\"<\/a>RapidMiner<\/a><\/strong> offers a unified platform for data science teams that includes data preparation, machine learning and predictive model deployment. The product touts a community of more than a quarter-million data science experts, as well as a marketplace that keeps pace with evolving trends. RapidMiner\u2019s 60+ connectors provide access to any type of data, and users can run workflows in-memory or in-Hadoop.<\/p>\n

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\"TIBCO<\/a>TIBCO<\/a><\/strong>\u2019s product capabilities are expansive, and range from data integration and API management to visual analytics, reporting, and data science. The company\u2019s BI and analytics portfolio comes in two main iterations: TIBCO Spotfire and TIBCO Jaspersoft. TIBCO Spotfire is the company\u2019s more modern platform. It features interactive visualization, data preparation, enterprise-class governance, and advanced analytic capabilities. TIBCO Jaspersoft supports traditional reporting and embedded BI functionality.<\/p>\n

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\"KNIME\"<\/a>KNIME<\/a><\/strong> offers an open-source analytics platform for intuitive, integrative data science. It also licenses KNIME Server, a tool for productionalizing data science by offering functionality for collaboration, automation, deployment and management.\u00a0KNIME features more than 1500 modules, hundreds of ready-to-run examples, and a wide set of advanced algorithms. The company was founded in 2008.<\/p>\n

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\"SAS\"<\/a>SAS<\/a><\/strong> Visual Analytics is available on-prem or in the cloud. Visual Analytics allows users to visually explore data to automatically highlight key relationships, outliers, and clusters. Users can also take advantage of advanced visualizations and guided analysis through autocharting. SAS has made its name as a result of advanced analytics, as the tool can ingest data from diverse data sources and handle complex models.<\/p>\n

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Data science and machine learning platforms come in a variety of shapes and sizes to meet the ever-changing needs of organizations and their increasingly complex big data environments. Businesses require data solutions that can serve any number of different use cases, and in the case of data science, can range from predictive analytics to natural […]<\/p>\n","protected":false},"author":23,"featured_media":4374,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[828,397,39,154,127,155,152,680],"acf":[],"yoast_head":"\nThe 4 Major Players in Data Science and Machine Learning Platforms, 2019<\/title>\n<meta name=\"description\" content=\"These four providers have recently been named major players in data science and machine learning platforms by analyst house Gartner, Inc.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/solutionsreview.com\/business-intelligence\/the-4-major-players-in-data-science-and-machine-learning-platforms-2019\/\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Tim King\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/solutionsreview.com\/business-intelligence\/the-4-major-players-in-data-science-and-machine-learning-platforms-2019\/\",\"url\":\"https:\/\/solutionsreview.com\/business-intelligence\/the-4-major-players-in-data-science-and-machine-learning-platforms-2019\/\",\"name\":\"The 4 Major Players in Data Science and Machine Learning Platforms, 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