Data Science Platforms Market Decoded in a Recent Research Report —
The global data science platform market size is anticipated to reach over USD 178 billion by 2025. Despite infancy the global data science platform market is likely to remain overtly lucrative in the forthcoming years owing to large scale adoption across enterprises. Conventionally, a data science platform is an elaborate software compilation that designs and directs data science activities. Adroit Market Research in its recent research offering on data science platform market, takes a closer look into ongoing market developments, emerging trends and corporate developments that collectively direct steady growth and sustainability in global data science platform market.
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Data science platform is a holistic compilation of software that enable data integration and exploration from a myriad data sources, followed by efficient decoding of the same to enable improved data applications. Advances in data based economy is likely to foster high potential growth in data science platforms space.
Leading players in data science platforms market are investing towards developing new age data science platforms to align with emerging business needs. Therefore, funding remains a core development area amongst leading participants in data science platforms market. To cite an appropriate instance in this regard, Deepnote, best known for its disruptive cloud based data science platforms dedicated for data scientists has recently announced its successful fund collection of around $4 million from renowned venture capitalists such as Accel and Index Ventures to further improve its data science platforms aiding data scientists.
Further in data science platform market, to align with soaring business demands and fast growing competition, data science platform provider, Cnvrg.io has recently made available a free version of its data science platform, under the brand, CORE, enabling building, managing, and automating ML models.
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Based on systematic segmentation global data science platform market is fragmented into platform, application, and industry vertical. BY platform, global data science platform market is splintered into solutions, services, managed and professional services. Based on application the market is classified into logistics, marketing, sales, HR, and customer support as major application practices in data science platform space. In terms of industry vertical, data science platform market is segregated into BFSI, IT and Telecom, healthcare, retail, and government and defense. Further, global data science platform market is also fragmented on the basis of regional diversification, identifying Europe, North and South America, MEA and APAC as major growth spots in data science platform market.
A dedicated section on competition spectrum is also tagged in the concluding sections of the report to invoke lucrative business discretion in data science platform market. Some of the frontline players in the market comprise, Microsoft, Google, IBM, Wolfram, and SAS besides several others in the league.
Key Segments of the Global Data Science Platform Market
Platform Overview, 2018-2025 (USD Billion)
Application Overview, 2018-2025 (USD Billion)
Industry vertical Overview, 2018-2025 (USD Billion)
IT & Telecom
Government & Defense
Regional Overview, 2018-2025 (USD Billion)
Middle East and Africa
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Adroit Market Research is an India-based business analytics and consulting company incorporated in 2018. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a market's size, key trends, participants and future outlook of an industry. We intend to become our clients' knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code - Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps.
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