The global data science platform market was worth USD 32.93 billion in 2023. The global market is estimated to be USD 43.73 billion in 2024 and USD 423.02 billion by 2032, growing at a CAGR of 32.8% during the forecast period.
A Data Science Platform is software that includes different types of technologies for machine learning and other advanced analytics uses. It is an environment for conducting data science work, which basically includes coding and deploying the code models as well as aggregation and use of data from various resources. Data Science provides a structure in which the entire lifecycle of the data science projects takes place. This platform consists of the tools and resources which is required to complete each phase of the data science project lifecycle. It brings together people, tools, resources, and other necessary products that are used across the data science lifecycle from development to deployment. Data science allows all the resources to be centralized and allows data scientists and teams to speed up the model deployment process. The data science platform helps organizations find when and where their products sell best. It can also help deliver the right product at the right time and help the company develop new products to meet customers' demands. Owing to the various features and benefits to the business, the demand for the data science platform is going to increase, which will further boost the growth of the data science platform market.
Telecom companies mainly function with broad communication networks and infrastructure and thus operate in the full data flow. Therefore, the need for data science is increasing in this sector in order to analyze and process large volumes of data effectively and efficiently. Further, the cloud is catering to market adoption with data science platform integration, where major players are significantly developing the cloud integration platform. For example, Google Cloud offers a platform which is called “BigQuery.” BigQuery is a serverless and scalable data warehouse that offers data scientists the ability to store and analyze petabytes of data on a single platform.
The rising awareness of the benefits of data science in business is driving the demand for a data science platform in developed and developing nations around the world.
Furthermore, during the pandemic, cloud computing has emerged as an efficient model that helps facilitate some of the most crucial transformations businesses are undergoing. According to the cloud surveys conducted by Flexera, globally, around 50% of organizations, including both SMBs and enterprises, plan to increase their cloud usage in light of the coronavirus crisis; the demand for the data science platform will increase in the near future.
A data scientist is skilled enough to better utilize all the tools and resources of a data science platform to get the best results and organizational growth. The lack of such desired skilled scientists is hampering the growth of the data science platform market.
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REPORT METRIC |
DETAILS |
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Market Size Available |
2023 to 2032 |
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Base Year |
2023 |
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Forecast Period |
2024 to 2032 |
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CAGR |
32.8% |
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Segments Covered |
By Services, Business Function, Mode of Deployment, Industry, and Region. |
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Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
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Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
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Market Leaders Profiled |
IBM Corporation (US), Microsoft Corporation (US), Alphabet Inc. (Google) (US), Altair Engineering, Inc. (US), Alteryx, Inc. (US), MathWorks (Australia), SAS Institute Inc. (US), RapidMiner, Inc. (US), Cloudera, Inc. (US), Anaconda, Inc. (US) and Others. |
Based on Services, the Data Science Platform Market is segmented into Managed Services and Professional Services. Professional Service segment is expected to dominate the market due to growing complexity of operations and the increasing deployment of Business Intelligence platform.
Based on Business Function, the Marketing and Sales segment holds the largest market share because using data science in marketing and sales departments can get more insights into the buyer’s mind and spend the marketing budget accordingly, thereby generating more Return on Investment (ROI). In addition, the other factors, such as reduced financial risks due to precise spending calculation, more predictable revenue generation, and enhanced customer experience, contribute to the adoption of Data Science in this segment, which will boost the Data Science Platform during the forecast period.
Based on the mode of deployment, the Data Science Platform Market is segmented into Cloud and On-Premises. The cloud segment is expected to dominate the market during the forecast period due to the deployment of a cloud-based data science platform that helps businesses more efficiently process and report data findings; it enhances collaborations and provides decision-makers faster access to business intelligence. Owing to these benefits, the cloud segment drives the growth of the data science platform market in the coming years.
Based on Industry, the Data Science Platform Market is segmented into Banking, Financial Services & Insurance (BFSI), Telecom and IT, Retail and e-commerce, Healthcare and Life sciences, Manufacturing, Energy and Utilities, Media and Entertainment, Transportation and Logistics, Government and Others. Among these sectors, the healthcare segment is expected to dominate the market in the upcoming years. Data science platform provides various medical research communities that can generally share, integrate, and analyze historical, patient-level data from academic and industry phase III clinical trials. Owing to such a rich data set as a part of data science that undoubtedly will help pharmaceutical research and development segment.
The Global Data Science Platform Market has been categorized into four regions: North America, Europe, Asia-Pacific, and RoW (Rest of the World).
North America accounted for the largest market share and will continue to dominate the market during the forecast period due to large enterprises, technical experts, and the increasing demand for data platforms in this region. In the United States, a large number of clinical documents are produced annually, and healthcare practitioners and doctors have significant data upon which to base their research. Moreover, a huge volume of health-related information is made accessible through the large adoption of wearable technologies in this region, thus bringing new opportunities for the region's better and more informed healthcare system. Furthermore, the presence of capital-intensive industries across this region proves to be beneficial for the growth of the data science platform. Additionally, the presence of some of the established players, such as Google Inc., IBM Corporation, Microsoft, Cloudera, etc., are leveraging powerful machine learning and data science technologies that can turn data into actionable insights, further driving the growth of the data science platform market during the forecast period.
After North America, Europe holds the largest share of the Data Science Platform Market due to rising data-driven digital transformation. A large number of industries are adopting these technologies in their systems, driving the growth of the market.
Asia-Pacific is expected to become the fastest growing market due to increasing demand of data processing is boosting the demand of the data science platform in this region. Moreover, the investments by the major companies are driving the growth of the data science market in this region. Also, with the increasing awareness of the benefits of these platforms, enterprises have started integrating data science platforms into their existing operation system in order to gain a competitive advantage in the region marketplace place, which further drives the demand for data science platforms in this region. In this region, China is actively investing in the data science sector while implementing the technologies.
Some of the leading companies operating in the Global Data Science Platform Market are
By Services
By Business Function
By Mode of Deployment
By Industry
By Region
Frequently Asked Questions
Essential features of a Data Science Platform include advanced analytics capabilities, scalability to handle large volumes of data, integration with existing IT infrastructure, support for multiple programming languages such as Python and R, robust security features, and user-friendly interfaces for data visualization and exploration.
Data Science Platforms are in high demand across various industries including banking and finance, healthcare, retail, manufacturing, telecommunications, and e-commerce. These sectors are leveraging data science and analytics to optimize operations, improve customer experiences, mitigate risks, and drive innovation.
Data Science Platforms provide the necessary tools and infrastructure for developing, training, and deploying AI and machine learning models at scale. These platforms enable data scientists and developers to experiment with different algorithms, perform feature engineering, and leverage large datasets to train accurate and predictive models, thereby advancing the field of AI and machine learning.
Edge computing is driving the decentralization of data processing and analysis, enabling real-time insights and decision-making at the network edge. Data Science Platforms are adapting to support edge analytics capabilities, allowing organizations to derive insights from data generated by IoT devices, sensors, and other edge endpoints, thereby unlocking new use cases and business opportunities.
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