The global data science platform market size is expected to reach USD 470.92 billion in 2030 and is projected to grow at a CAGR of 26.0% from 2024 to 2030. Technological advancements such as integration of Natural Language Processing (NLP) and Machine Learning (ML) are at a remarkably quick pace. Companies such as Microsoft Corporation today are shifting towards the adoption of high-level strategies to gain a competitive edge in the market. With rapid transformation, data has become a very critical asset for any organization. Thus, it has become essential for companies to look for data science teams to gain substantial insights from the gathered data.
Numerous data science teams have grown out of their existing tools and are experiencing a lack of collaboration and scalability as they become overpowered by commonplace operational errands. To overcome this problem, companies are now opting for data science platforms that are modular or open, collaborative, scalable, multi-user, and support the entire pipeline of production. Factors such as business optimization, model deployment, model sharing, model management, scalability, reproducibility, and agility provided by these platforms have substantially contributed to rapid adoption.
Data science has become very critical for business today. As the number of tools, models, and model creators is increasing, the need for a uniform data science platform that can provide comprehensive solutions is increasing. To understand which tool to use when and manage the complexity associated with managing a vast quantity of data and gain flexibility, the adoption of these platforms is increasing. These platforms are providing companies with an end-to-end process of managing, deploying, and creating analytics models in a collaborative and open environment.
Further, the COVID-19 outbreak has also impacted the market tremendously. The emergence of new data and data patterns has changed the market scenario. Apart from changing data analysis models, it has provided a wide opportunity for data scientists to make use of advanced tools and techniques to help businesses make better decisions in such an environment that is uncertain, speedy, and lacks data. Also, data science platforms have assisted several companies in harnessing insights from the data and speed up the process of medical research.
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Increasing demand for a platform that can optimize mundane operational tasks and provide effective collaboration has driven the adoption.
The platform segment held the largest market revenue share of 83.9% in 2023 and is expected to continue leading the market over the forecast period. This is due to benefits such as reduced risk, improved customer satisfaction, and others provided by the platform.
The North America regional market is expected to hold a high revenue share over the forecast period, majorly due to the increasing demand for advanced technology platforms that can help to unlock critical insights from a vast amount of data being generated every day.
Grand View Research has segmented the gloabl data science platform market report based on product, application, vertical, and region:
Data Science Platform Type Product (Revenue, USD Million, 2018 - 2030)
Platform
Services
Data Science Platform Application Outlook (Revenue, USD Million, 2018 - 2030)
Marketing and Sales
Logistics
Finance and Accounting
Customer Support
Others
Data Science Platform Vertical Outlook (Revenue, USD Million, 2018 - 2030)
IT & Telecommunication
Healthcare
BFSI
Manufacturing
Retail
Energy and Utilities
Government
Others
Data Science Platform Regional Outlook (Revenue, USD Million, 2018 - 2030)
North America
U.S.
Canada
Mexico
Europe
UK
Germany
Asia Pacific
China
India
Japan
Australia
South Africa
Latin America
Brazil
Middle East and Africa (MEA)
South Africa
Saudi Arabia
UAE
List of Key Players in Data Science Platform Market
Google LLC
Microsoft
IBM Corporation
H2O.ai.
Oracle
Alteryx
Cloud Software Group, Inc.
SAS Institute Inc.
SAP
The MathWorks, Inc.
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