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Data Science Platform Market Share

ID: MRFR//3763-HCR | 100 Pages | Author: Ankit Gupta| April 2024

The Data Science Platform market is now seeing dynamic patterns caused by the growing importance of data-driven navigation and enterprise adoption of cutting-edge research. This industry has a clear trend of start-to-finish data science platforms that streamline the work process. Data preparation, model sequence of events, transmission, and observing platforms help data researchers operate efficiently. Coordination platforms are needed to speed up AI model development and gain valuable insights from data more consistently and cooperatively.

Data Science Platform market trends are shaped by open-source devices and architectures. Associations build and transmit AI models using Python, R, and TensorFlow. Data science platforms that connect to open-source innovations are making progress, allowing organizations to harness the power of the larger data science community and benefit from open-source arrangements' adaptability and customization.

Data science democratization is another major business trend. As organizations realize the benefits of making data science capabilities available to more clients, data science platforms are becoming more user-friendly and collaborative. Low-code and no-code platforms are becoming common, allowing non-specialists to analyze data and model outcomes. This pattern is designed to encourage corporate clients to make data-driven decisions without advanced skills.

Increasing emphasis on AI model interpretability and reasonableness is shaping Data Science Platform markets. AI models are becoming more complex, thus they need simpler decision-making. Data scientists and business clients may better understand, decode, and trust AI model findings thanks to data science platforms' features that provide insights on the behavior of models. Enterprises with administrative consistency requirements and moral man-made intelligence practices need this pattern.

Cloud-based Data Science Platform arrangements are improving. Cloud solutions provide flexible processing, lower infrastructure costs, and collaboration among geographically dispersed teams. Data science systems with consistent cloud integration are becoming popular, allowing companies to use distributed computing for data science initiatives. The industry's wider transition to cloud reception for IT capabilities matches this tendency.

Covered Aspects:

Report Attribute/Metric Details
Base Year For Estimation 2022
Historical Data 2019 - 2021
Forecast Period 2023-2030
Growth Rate 19.20% (2023-2030)

Data Science Platform Market Overview


Data Science Platform Market Deployment was valued at USD 100.9 billion in 2022. The Data Science Platform market industry is projected to grow from USD 120.27 Billion in 2023 to USD 345.0 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 19.20% during the forecast period (2023 - 2030). Technological advancements are happening rapidly with increasing investments in R&D. As businesses grow, so does the need for technologies that increase productivity and efficiency. These are the key market drivers enhancing market growth.


Figure 1: Data Science Platform Market Size, 2022-2030 (USD Billion)


Data Science Platform Market Overview


Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Data Science Platform Market Trends



  • Numerous Benefits offered by Data Science Platforms to boost the market growth


Data science platforms are currently being used increasingly due to the various benefits these platforms offer. The software provides open-source tools with remarkable flexibility and scalability of computing resources. Also, it's easy to be consistent with different data schemas. Additionally, the platform supports version control, enabling data science teams to collaborate on projects without losing recently completed work. Hence, these advantages significantly contribute to market expansion during the forecast period.


Furthermore, factors such as surging reliance on machine learning and the surging propensity of enterprises for data-intensive business strategies will accelerate the overall market expansion over the forecast period. Furthermore, the surging adoption of cloud-based solutions and services is expected to drive the Growth of the data science platform market. Increased demand for analytical tools will further positively impact the market growth rate during the forecast period.


Increasing R&D investment is estimated to bring lucrative opportunities to the market, which will further expand the growth rate of the data science platform market in the future. Moreover, advancements in technologies such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) further provide numerous growth opportunities for the market. These are essential factors driving the Data Science Platform market revenue growth.


Data Science Platform Market Segment Insights



  • Data Science Platform Business Function Insights


Based on Business Function, the Data Science Platform market segmentation includes marketing, sales, logistics, and human resources. The sales classified segment held the majority share in 2022, contributing most of the Data Science Platform market revenue due to the various advantages offered, such as the use of data science, marketing, and sales departments can gain a deeper understanding of buyer personas and spend marketing budgets accordingly, generating more return on investment (ROI). Apart from this, factors such as reduced financial risk due to precise expense calculation, more predictable revenue generation, and enhanced customer experience contribute to the platform's adoption in this segment.


Data Science Platform Deployment Insights


Deployment has bifurcated the Data Science Platform market data into on-demand and on-premises. On-Premise has a considerable share of the market. Cloud computing refers to storing, managing, and processing data via networks of remote servers, which are typically accessed via the Internet. Enterprises mostly in heavily regulated industry verticals, such as BFS, healthcare and life sciences, and manufacturing, Opt for the on-premises deployment model of a Data Science Platform. Furthermore, large enterprises with sufficient IT resources are expected to opt for the on-premises deployment model. On-premises is the most reliable deployment mode, which an enterprise can rely on for a high level of control and security. Enterprises need to purchase a license or a copy to deploy cloud-based solutions.


Figure 2: Data Science Platform Market by Verticals, 2022 & 2030 (USD billion)Data Science Platform Market by Verticals, 2022 & 2030


Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review


Data Science Platform Verticals Insights


Based on Verticals, the Data Science Platform industry has been segmented into BFSI, healthcare, retail, IT, and transportation. The healthcare segment is expected to grow over the forecast period. One of the major applications of the platform is medical imaging. The strong focus on advancing healthcare services has contributed to the rapid adoption of technology in the field.


Data Science Platform Regional Insights


By Region, the study provides market insights into North America, Europe, Asia-Pacific, and the Rest of the World. The North American Data Science Platform market, which accounted for USD 37.1 billion in 2022, is expected to exhibit a significant CAGR growth during the study period. This is due to the increasing focus of key market players in the Region on further developing these platforms. For example, in February 2020, technology company Oracle announced the launch of a cloud-based data science platform. New platform capabilities include audibility, reproducibility, team security policies, model catalogs, and shared projects.


Further, the significant countries studied in the market report are The U.S., Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.


Figure 3: DATA SCIENCE PLATFORM MARKET SHARE BY REGION 2022 (%)DATA SCIENCE PLATFORM MARKET SHARE BY REGION 2022


Source: Secondary Research, Primary Research, MRFR Database, and Analyst Review


Europe's Data Science Platform market accounts for the second-largest market share. With the rise of data-driven digital transformation, more and more companies in the Region are adopting the technology to drive Growth. The market in Asia Pacific is expected to register the highest CAGR during the forecast period. Increasing lifetime value, cost of acquisition, and customer retention drive this Growth. Further, the German Data Science Platform market held the largest market share, and the U.K. Data Science Platform market was the fastest-growing market in the European Region.


The Asia-Pacific Data Science Platform Market is expected to grow at the fastest CAGR from 2022 to 2030. The Growth of the industry in the Region is primarily driven by factors such as rising spending on big data technologies in economies such as India and China, surging mobile data traffic resulting in rapidly increasing volume and complexity, and emerging markets—application of IoT and artificial intelligence in business operations. Moreover, the China Data Science Platform market held the largest market share, and the Indian Data Science Platform market was the fastest-growing market in the Asia-Pacific region.


Data Science Platform Key Market Players & Competitive Insights


Major market players are spending a lot on R&D to increase their Verticals lines, which will help the Data Science Platform market grow even more. Market participants are also taking various strategic initiatives to grow their worldwide footprint, with key market developments such as new Verticals launches, contractual agreements, mergers and acquisitions, increased investments, and collaboration with other organizations. Data Science Platform industry competitors must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.


Manufacturing locally to reduce operating costs is one of the primary business strategies manufacturers adopt in the Data Science Platform industry to benefit clients and expand the market sector. The Data Science Platform industry has provided medicine with some of the most significant benefits in recent years. In the Data Science Platform markets, major players such as Microsoft Corporation (U.S.), IBM Corporation (U.S.), Google Inc. (U.S.), Wolfram (U.S.), and others are working on expanding the market demand by investing in research and development activities.


Google LLC is an American multinational technology company focused on online advertising, search engine technology, cloud computing, computer software, quantum computing, e-commerce, artificial intelligence, and consumer electronics. Due to its market dominance in artificial intelligence, data collection, and technological superiority, it has been called "the world's most powerful company" and one of its most valuable brands. In May 2021, Google changed the goals of Google Vertex AI, Google Cloud's new managed ML platform, to simplify the Deployment and maintenance of AI models for developers. The fact that Google chose to launch Vertex today shows how important the company thinks this new service will be for developers of all kinds. It's an unusual announcement at Google I/O, which usually focuses on mobile and web developers and doesn't usually include much Google Cloud news.


Also, International Business Machines Corporation (IBM), nicknamed Big Blue, is an American multinational technology corporation headquartered in Armonk, New York, with operations in over 175 countries. It focuses on computer hardware, middleware, and software and provides hosting and consulting services in areas ranging from mainframe computing to nanotechnology. IBM is the world's largest industrial research institution, with 19 research institutions in more than a dozen countries, and has held the record for the most annual U.S. patents by an enterprise for 29 consecutive years from 1993 to 2021.


Key Companies in the Data Science Platform market include




  • Microsoft Corporation (U.S.)




  • Sense Inc. (U.S.)




  • IBM Corporation (U.S.)




  • Wolfram (U.S.)




  • Google Inc. (U.S.)




  • DataRobot Inc. (U.S.)




  • RapidMiner Inc. (U.S.)




  • Domino Data Lab (U.S.)




  • Dataiku (France)




  • Alteryx Inc. (U.S.)




  • Continuum Analytics Inc. (U.S.)., among others




Data Science Platform Industry Developments


September 2021: Optimizely, a provider of digital experience platform solutions, announces the launch of Data Core Services to enhance the Digital Experience Platform (DXP) with deeper analytics and unified data insights across its product suite. With Data Core Services, companies better understand their customers and their overall digital business performance.


Data Science Platform Market Segmentation


Data Science Platform Business Function Outlook




  • Marketing




  • Sales




  • Logistics




  • Human Resources




Data Science Platform Deployment Outlook




  • On-Demand




  • On-Premises




Data Science Platform Verticals Outlook




  • BFSI




  • Healthcare




  • Retail




  • It




  • Transportation




Data Science Platform Regional Outlook




  • North America








    • US




    • Canada








  • Europe








    • Germany




    • France




    • UK




    • Italy




    • Spain




    • Rest of Europe








  • Asia-Pacific




    • China




    • Japan




    • India




    • Australia




    • South Korea




    • Australia




    • Rest of Asia-Pacific






  • Rest of the World




    • Middle East




    • Africa




    • Latin America





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