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Data Science Platform Market Aims to Expand at Double-Digit Growth Rate


 
Edison, NJ (SBWIRE) 12/24/2020 A new business intelligence report released by HTF MI with title Global Data Science Platform Market Report 2020 by Key Players, Types, Applications, Countries, Market Size, Forecast to 2026 (Based on 2020 COVID-19 Worldwide Spread) is designed covering micro level of analysis by manufacturers and key business segments. The Global Data Science Platform Market survey analysis offers energetic visions to conclude and study market size, market hopes, and competitive surroundings. The research is derived through primary and secondary statistics sources and it comprises both qualitative and quantitative detailing. Some of the key players profiled in the study are KNIME AG, GoogleInc., TIBCO Software India Pvt. Ltd, IBM Corporation, Microsoft Corporation, RapidMinerInc., AlteryxInc., Domino Data LabInc., Dataiku, Wolfram Research, SAS InstituteInc., BRIDGEi2i Analytics Solutions Pvt. Ltd, ClouderaInc., AnacondaInc, Teradata Corporation, H2O ....

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Global Data Science Platform Market (2020 to 2026) - by Component, Deployment Type, Enterprise Size, Application, End-user & Region


Global Data Science Platform Market (2020 to 2026) - by Component, Deployment Type, Enterprise Size, Application, End-user & Region
December 17, 2020 11:13 ET
| Source:
Research and Markets
Research and Markets
Dublin, IRELAND
ResearchAndMarkets.com s offering.
The Global Data Science Platform Market size is expected to reach $165.5 billion by 2026, rising at a market growth of 27% CAGR during the forecast period. The data science platform can be considered as a technology of software that is being extensively utilized by industries today. This software includes several innovations for numerous advanced analytics and machine learning. It enables data scientists to design strategies, uncover insights from data, and impart those experiences all through a venture inside a single situation. The projects performed in data science include numerous instruments designed at each step of the data modeling process ....

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