Data Science Platform Market Statistics: 2030
The global data science platform market was valued at $4.7 billion in 2020, and is projected to reach $79.7 billion by 2030, growing at a CAGR of 33.6% from 2021 to 2030.
Increase in reliance on machine learning creates a need for data science platforms that fulfill needs in building, training, scaling, and deploying machine learning (ML) models. The proper platforms and technologies enable breakthroughs in data science. In addition, machine learning and artificial intelligence are driving innovations in data science and data management. The advancement of big data technology and importance of collecting and using data for decision making are anticipated to drive the Data Science Platform Industry growth during the forecast period. However, high investment cost, data privacy & security, and reliability issues observed by the employees hamper the data science platform market growth. Moreover, adoption of cloud-based solutions & services and targeting untapped and emerging market for data science platforms are expected to provide ample growth opportunities for the market during forecast period.
Data science platform is a packaged software application that provides the tools for the entire life cycle of a data science project. Data science platforms are indispensables tools for data scientists. It enables data exploration, model development, and model distribution. It facilitates data preparation and data visualization while providing a large-scale computing infrastructure. Data science platforms help users collaborate by providing a centralized platform. They serve as a one-stop shop for data modeling because data science platforms contain the APIs to allow for model production and testing with minimal outside engineering needs.
Segment Review
Data science platform market is segmented on the basis of component, application, industry vertical, and region. On the basis of component, it is divided into platform and services. On the basis of application, it is divided into marketing & sales, logistics, finance and accounting, customer support, and others. According to the industry vertical, it is segmented into BFSI, IT & telecommunication, retail & E-Commerce, healthcare, transportation, manufacturing and others). Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
On the basis of component, the platform segment dominated the data science platform market share in 2020 and is expected to maintain its dominance in the forecast period. This is due to the increase in adoption of data science platforms in small and medium enterprises (SMEs). Companies move toward digitization and automation, which accelerate big data and lead to more complex business processes. To deal with these complexities, companies need cutting-edge technologies that enable them to gain real-time insights across vast data pools. The data science platform helps them streamline business processes and gain new customers. However, the services segment is expected to witness highest growth rate during the forecast period.
By end user, the BFSI segment dominated the data science platform market share in 2020, and is expected to maintain its dominance in the forecast period. This is due to digitalization of BFSI segment, rapid adoption of machine learning, artificial intelligence techniques for data management, and to enhance customer experience. However, manufacturing segment is expected to witness considerable growth rate during the forecast period. The modern manufacturing industry uses data science for increasing its productivity, reducing energy costs, and boosting production. Data provides manufactures with valuable insights for profit maximization, risk minimization, large scale production, and execution time acceleration.
Region wise, North America dominated the data science platform industry in 2020. Growth of the market in this region is attributed to several factors, such as rapid digitalization along with the surge in government funding on innovative technologies, increase in number of IoT devices, and growth in technical base. However, Asia-Pacific is expected to witness highest growth rate during the forecast period, owing to large investments by key players in the region. For instance, as per recent studies, Asia-Pacific expenditure for big data and analytics solutions increased to about $22.7bn in 2020, with three out of four companies intending to keep or expand their big data analytics investments.
Top Impacting Factors
Data Explosion
Data is growing in an exponential manner. About 90% of the data that currently exists in the world has been created in the past few years. The massive increase in data creates opportunities for organizations to gain new insights, for which the demand for new techniques and methods are increased. This, in turn, plays a very crucial role to drive the data science platform market size.
Realization of Importance of Data Science Platform by Organizations
Data science platforms help organizations to be proactive and predictive. It allows them to take actions to optimize outcomes rather than being reactive. Many organizations and start-ups have been benefitted using data science platforms. Some examples include PayPal using big data analytics to detect fraud, pharma industry building better medicines at a faster pace using data science tools, and many retail companies customizing individual customer preferences and building products that meet their expectations using data analysis. Organizations become data driven and invest in infrastructure, people, and processes to initiate a data science journey.
Key Benefits for Stakeholders
- This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the global data science platform market analysis from 2020 to 2030 to identify the prevailing global data science platform market opportunities.
- The data science platform market research is offered along with information related to key drivers, restraints, and opportunities.
- Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
- In-depth analysis of the global data science platform market segmentation assists to determine the prevailing market opportunities.
- Major countries in each region are mapped according to their revenue contribution to the global market.
- Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the data science platform market players.
- The report includes the analysis of the regional as well as global global data science platform market trends, key players, market segments, application areas, and market growth strategies.
Global Data Science Platform Market Report Highlights
| Aspects | Details |
 By Component |
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 By Application |
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 By Industry Vertical |
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 By Region |
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 Key Market Players | TERADATA CORPORATION, DATAIKU SAS, RAPIDMINER INC, MICROSOFT CORPORATION, FAIR ISSAC CORPORATION (FICO), INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM CORPORATION), SAS INSTITUTE INC., SAP SE, THE MATHWORKS INC, ALTREYX, INC. |
Analyst Review
In accordance with the insights by the CXOs of leading companies, the global data science platform market is projected to witness prominent growth, especially in Asia-Pacific and LAMEA. This growth is attributed to surge in digitization and the increase in trend of data-driven decision making among end-user companies. Prominent players that operate in the data science platform market industry focus on introducing advanced data analytics solutions equipped with high-definition graphics features that enable users to procure the insights faster and accurately.
Data science platforms are packaged software applications that provide the tools for the entire life cycle of a data science project. Data science platforms are indispensables tools for data scientists. It enables data exploration, model development, and model distribution. They also facilitate data preparation and data visualization while providing a large-scale computing infrastructure. Data science platforms help users collaborate by providing a centralized platform. They serve as a one-stop shop for data modeling because data science platforms contain the APIs to allow for model production and testing with minimal outside engineering needs.
In addition, the cloud platforms gained immense popularity due to storage, management ,and data processing through remote networks. As per Statista, cloud computing, had revenue of more than $300 billion in 2020 as a component of IT services.
Moreover, growth in reliance on machine learning created a need for data science platforms that fulfill needs in building, training, scaling and deploying machine learning (ML) models. The proper platforms and technologies enable breakthroughs in data science. In addition, Machine learning and artificial intelligence are driving innovations in data science and data management. For instance, in December 2021, Teradata has announced a new set of analytic integration components for the “everyday AI” platform Dataiku. The new Teradata Plugins for Dataiku are designed to enable analytics and data science teams that use Dataiku to implement a wide range of analytic functions within the Teradata Vantage platform.
Data science platform market was valued at $ 4,705.21 million in 2020
Increase in reliance on machine learning creates a need for data science platforms that fulfill needs in building, training, scaling, and deploying machine learning (ML) models. The proper platforms and technologies enable breakthroughs in data science.
Marketing & Sales
North America dominated the global market
The global data science platform market is dominated by key players such as Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku, Alteryx, Inc., FICO, The MathWorks, Inc., and Teradata.
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