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Data Science Platform Market Trends

ID: MRFR/ICT/3763-HCR
100 Pages
Ankit Gupta
October 2025

Data Science Platform Market Research Report Information By Business Function (marketing, sales, logistics, and human resources), By Deployment (on-demand and on-premises), By Verticals (BFSI, healthcare, retail, IT and transportation), And By Region (North America, Europe, Asia-Pacific, And Rest Of The World) – Market Forecast Till 2035.

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Market Trends

Key Emerging Trends in the Data Science Platform Market

Organizations use several methods to minimize their market offer and acquire an edge in the strong Data Science Platform industry. A focus process involves separation, where companies want to stand apart by delivering unique features and high-level capabilities in their data science platforms. It might include robust AI computations, intuitive UIs, or a constant mix of data instruments. Companies strive to attract clients searching for certain features and establish themselves as high-quality data science providers through separation to build client loyalty.

Cost authority is another important Data Science Platform market mechanism. By improving operational efficiency, using economies of scale, and conducting productive expense board practices, organizations try to make smart decisions. This strategy attracts budget-conscious customers and boosts market share. By offering powerful data science platforms at low prices, cost-conscious companies hope to become the top choice for companies seeking affordable but powerful data science solutions.

Market division is crucial to Data Science Platform companies' market share positioning strategies. Companies customize their platforms to meet the needs of different businesses. This involves developing marketing and sales strategies and providing specific solutions. Market division allows companies to specialize in specialized areas, expanding their customer base and market share.

Key partnerships are becoming more common in the Data Science Platform sector. Organizations understand the benefits of partnering with innovation, data, or industry experts to improve platform contributions. Cooperative efforts let companies expand their platforms, enter new markets, and profit from correlation. Organizations increase market share by expanding clientele and increasing cooperation.

industry share positioning in the Data Science Platform industry requires strong branding and marketing. Laying forth a picture's strengths builds credibility and recognition. Companies sell their uniqueness, reliability, and resilience. A strong brand presence attracts new customers and strengthens existing ones, helping to grow market share.

Continuous development underpins the Data Science Platform industry. Organizations invest in innovation to better their platforms. This might contain trend-setting advances like normal language processing, automated model sending, or better collaborative effort highlights. Creative solutions meet customer needs and position companies as industry leaders, attracting associations that focus on cutting-edge and future-ready data science platforms.

Author
Ankit Gupta
Senior Research Analyst

Ankit Gupta is an analyst in market research industry in ICT and SEMI industry. With post-graduation in "Telecom and Marketing Management" and graduation in "Electronics and Telecommunication" vertical he is well versed with recent development in ICT industry as a whole. Having worked on more than 150+ reports including consultation for fortune 500 companies such as Microsoft and Rio Tinto in identifying solutions with respect to business problems his opinions are inclined towards mixture of technical and managerial aspects.

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FAQs

How much is the Data Science Platform market?

The Data Science Platform market was valued at USD 100.9 Billion in 2022.

What is the growth rate of the Data Science Platform market?

The market is projected to grow at a CAGR of 19.20% from 2023-2030.

Which Region held the largest market share in the Data Science Platform market?

North America had the largest share of the market.

Who are the key players in the Data Science Platform market?

The key players in the market are Microsoft Corporation (U.S.), IBM Corporation (U.S.), Google Inc. (U.S.), and Wolfram (U.S.).

Which Business Function led the Data Science Platform market?

The Sales category dominated the market in 2022.

Which Deployment had the largest market share in the Data Science Platform market?

On-Premises had the most extensive Data Science Platform market share.

Market Summary

As per MRFR analysis, the Data Science Platform Market Size was estimated at 140.1 USD Billion in 2024. The Data Science Platform industry is projected to grow from 163.99 USD Billion in 2025 to 947.97 USD Billion by 2035, exhibiting a compound annual growth rate (CAGR) of 19.18 during the forecast period 2025 - 2035.

Key Market Trends & Highlights

The Data Science Platform Market is experiencing robust growth driven by technological advancements and evolving user needs.

  • The market witnesses increased adoption of AI and machine learning, particularly in North America, which remains the largest market.
  • There is a notable focus on data governance and security, reflecting the rising importance of data privacy regulations across various sectors.
  • The rise of no-code and low-code platforms is transforming how organizations approach data science, especially in the fast-growing Asia-Pacific region.
  • Key market drivers include the growing demand for data-driven decision making and advancements in cloud computing technologies, particularly in predictive analytics and cloud-based segments.

Market Size & Forecast

2024 Market Size 140.1 (USD Billion)
2035 Market Size 947.97 (USD Billion)
CAGR (2025 - 2035) 19.18%
Largest Regional Market Share in 2024 North America

Major Players

<p>IBM (US), Microsoft (US), Google (US), SAS (US), Oracle (US), SAP (DE), Alteryx (US), DataRobot (US), TIBCO (US), RapidMiner (US)</p>

Market Trends

The Data Science Platform Market is currently experiencing a transformative phase, characterized by rapid advancements in technology and an increasing demand for data-driven decision-making across various sectors. Organizations are increasingly recognizing the value of harnessing data to gain insights, optimize operations, and enhance customer experiences. This shift is prompting a surge in the adoption of sophisticated data science platforms that facilitate the integration of machine learning, artificial intelligence, and big data analytics. As businesses strive to remain competitive, the emphasis on data literacy and the ability to extract actionable intelligence from vast datasets becomes paramount. Moreover, the Data Science Platform Market is witnessing a growing trend towards cloud-based solutions, which offer scalability, flexibility, and cost-effectiveness. Companies are gravitating towards platforms that provide collaborative environments, enabling teams to work together seamlessly, regardless of geographical barriers. This collaborative approach not only accelerates project timelines but also fosters innovation by allowing diverse perspectives to converge. As the landscape evolves, it appears that the Data Science Platform Market will continue to expand, driven by the relentless pursuit of efficiency and the need for organizations to adapt to an increasingly data-centric world.

Increased Adoption of AI and Machine Learning

Organizations are increasingly integrating artificial intelligence and machine learning capabilities into their data science platforms. This trend enhances predictive analytics and automates various processes, allowing businesses to derive insights more efficiently.

Focus on Data Governance and Security

As data privacy concerns grow, there is a heightened emphasis on data governance and security within the Data Science Platform Market. Companies are prioritizing compliance with regulations and implementing robust security measures to protect sensitive information.

Rise of No-Code and Low-Code Platforms

The emergence of no-code and low-code platforms is democratizing access to data science tools. This trend enables non-technical users to engage with data analytics, fostering a broader range of individuals to contribute to data-driven initiatives.

Data Science Platform Market Market Drivers

Market Growth Projections

The Global Data Science Platform Market Industry is poised for remarkable growth, with projections indicating a market size of 144.6 USD Billion in 2024 and an anticipated increase to 830.2 USD Billion by 2035. This trajectory suggests a compound annual growth rate (CAGR) of 17.22% from 2025 to 2035, reflecting the increasing reliance on data science platforms across various sectors. The convergence of technological advancements, regulatory demands, and the growing need for data-driven insights positions the market for sustained expansion in the foreseeable future.

Emergence of Big Data Technologies

The emergence of big data technologies significantly influences the Global Data Science Platform Market Industry. As organizations generate and collect unprecedented volumes of data, the need for advanced analytics solutions becomes paramount. Big data technologies enable the processing and analysis of large datasets, facilitating the extraction of meaningful insights that can inform business strategies. Companies that harness big data analytics can gain a competitive edge by identifying trends and patterns that may not be apparent through traditional data analysis methods. This growing emphasis on big data is likely to sustain market growth in the coming years.

Growing Adoption of Cloud-Based Solutions

The shift towards cloud-based solutions is a key driver of the Global Data Science Platform Market Industry. Organizations are increasingly migrating their data analytics operations to the cloud to benefit from scalability, flexibility, and cost-effectiveness. Cloud platforms allow businesses to access advanced data science tools without the need for significant upfront investments in infrastructure. This trend is particularly advantageous for small and medium-sized enterprises, which can leverage cloud-based data science platforms to compete with larger organizations. As cloud adoption continues to rise, the market is poised for substantial growth, with a projected CAGR of 17.22% from 2025 to 2035.

Regulatory Compliance and Data Governance

Regulatory compliance and data governance are becoming increasingly critical in the Global Data Science Platform Market Industry. Organizations must navigate complex regulations regarding data privacy and security, which necessitates the implementation of robust data governance frameworks. Data science platforms that offer built-in compliance features are gaining traction as businesses seek to mitigate risks associated with data breaches and non-compliance penalties. This focus on regulatory adherence not only enhances trust among consumers but also drives the demand for sophisticated data science solutions that can ensure compliance while delivering valuable insights.

Increasing Demand for Data-Driven Decision Making

The Global Data Science Platform Market Industry experiences a robust demand for data-driven decision-making processes across various sectors. Organizations increasingly recognize the value of leveraging data analytics to enhance operational efficiency and drive strategic initiatives. This trend is particularly evident in industries such as finance, healthcare, and retail, where data insights can lead to improved customer experiences and optimized resource allocation. As a result, the market is projected to reach 144.6 USD Billion in 2024, reflecting a growing reliance on data science platforms to inform critical business decisions.

Advancements in Artificial Intelligence and Machine Learning

Technological advancements in artificial intelligence and machine learning significantly propel the Global Data Science Platform Market Industry. These innovations enable organizations to automate complex data analysis and derive actionable insights with greater accuracy. For instance, AI-driven algorithms can process vast datasets in real-time, facilitating predictive analytics and enhancing decision-making capabilities. The integration of AI and machine learning into data science platforms is expected to contribute to the market's growth, with projections indicating a market size of 830.2 USD Billion by 2035, highlighting the transformative potential of these technologies.

Market Segment Insights

By Application: Predictive Analytics (Largest) vs. Machine Learning (Fastest-Growing)

<p>In the Data Science Platform Market, the application segments showcase a dynamic distribution of market share. Predictive Analytics stands out as the largest segment, capturing significant attention from businesses aiming to forecast future trends based on historical data. Following closely is the Machine Learning segment, which is rapidly gaining traction due to its innovative capabilities and the increasing demand for automation and smarter data solutions. As organizations increasingly recognize the value of data-driven decision-making, the growth trends within this market are robust. The popularity of Machine Learning is propelled by the surge of artificial intelligence, with firms eager to leverage sophisticated algorithms that enhance predictive performance. Meanwhile, Data Mining and Statistical Analysis remain essential for honing insights from complex datasets, further driving growth within the sector as they emphasize critical analytical skills.</p>

<p>Predictive Analytics (Dominant) vs. Data Mining (Emerging)</p>

<p>Predictive Analytics is characterized by its focus on utilizing historical data to forecast future outcomes, making it a critical tool for businesses seeking to optimize strategies and enhance operational efficiency. This dominant segment stands out due to its ability to inform risk management and marketing strategies effectively. On the other hand, Data Mining, labeled as an emerging segment, is vital for extracting usable information from extensive datasets. As companies increasingly gather large volumes of data, the need for Data Mining grows, positioning it as a crucial complement to Predictive Analytics. While Predictive Analytics often relies on Data Mining techniques, the latter focuses on identifying patterns and relationships in data, thus paving the way for more informed decision-making.</p>

By Deployment Model: Cloud-Based (Largest) vs. Hybrid (Fastest-Growing)

<p>The Data Science Platform Market is seeing a clear distinction in market share among its deployment models. Cloud-Based platforms currently dominate the market due to their scalability and flexibility, appealing to a wide range of businesses looking for efficient data solutions. On-Premises models hold a notable share but are gradually giving way to more agile alternatives. Hybrid models, which combine elements of both on-premises and cloud solutions, are carving out a significant niche as they address specific needs for customization and compliance, making them increasingly popular.</p>

<p>Cloud-Based (Dominant) vs. Hybrid (Emerging)</p>

<p>Cloud-Based deployment is characterized by its robust scalability, ease of access, and lower upfront costs, making it the preferred choice for organizations looking to leverage powerful data science capabilities without significant capital investment. As businesses continue to embrace digital transformation, Cloud-Based solutions stand out for their ability to integrate seamlessly with existing technologies and maximize collaborative efforts. In contrast, Hybrid deployment is gaining traction as organizations seek to balance the benefits of cloud scalability with the control and security of on-premises systems. This model allows them to manage sensitive data internally while still accessing advanced analytics tools available in the cloud, making it a flexible option for various industries.</p>

By End User: Large Enterprises (Largest) vs. Small and Medium Enterprises (Fastest-Growing)

<p>In the Data Science Platform Market, the distribution of market share among end users showcases a clear dominance of Large Enterprises, accounting for the largest portion of the market. These enterprises leverage advanced data analytics to enhance operations, optimize decision-making, and gain competitive advantages through data-driven insights. Conversely, Small and Medium Enterprises (SMEs) are rapidly emerging, fueled by the accessibility of cloud-based solutions and increasingly affordable data science tools that allow them to harness insights that were once only available to larger organizations.</p>

<p>Large Enterprises (Dominant) vs. Small and Medium Enterprises (Emerging)</p>

<p>Large Enterprises stand at the forefront of the Data Science Platform Market. Their substantial resources enable them to invest heavily in comprehensive data analytics solutions, empowering them to execute intricate data strategies at scale. They often implement dedicated teams of data scientists and analysts to extract actionable insights from vast datasets, significantly improving operational efficiency and strategic planning. On the other hand, Small and Medium Enterprises are characterized by their agility and innovation. With the rise of user-friendly and cost-effective data science platforms, SMEs are increasingly adopting these technologies to level the playing field. This trend is driving a surge in demand, positioning SMEs as the fastest-growing segment within the market, eager to utilize data for enhancing their business outcomes.</p>

By Functionality: Data Preparation (Largest) vs. Data Visualization (Fastest-Growing)

<p>In the Data Science Platform Market, the functionality segment exhibits a diverse distribution among its key components. Data Preparation holds the largest market share, driven by its fundamental role in ensuring high-quality data for analysis and modeling. On the other hand, Data Visualization, while smaller in share, has emerged as a vital tool among data scientists, enabling clear communication of complex insights through intuitive visual formats.</p>

<p>Data Preparation (Dominant) vs. Data Visualization (Emerging)</p>

<p>Data Preparation is critical in the Data Science Platform Market, providing tools for cleaning, transforming, and integrating data from various sources. Its dominance stems from organizations’ increasing emphasis on data quality, which serves as a foundation for effective model building and analysis. Meanwhile, Data Visualization, labeled as an emerging player, is rapidly gaining traction. As data becomes more complex, the demand for robust visualization tools that facilitate decision-making is surging. These tools empower data scientists to create compelling narratives around their findings, fostering a culture of data-driven decision-making.</p>

Get more detailed insights about Data Science Platform Market Research Report - Global Forecast to 2035

Regional Insights

North America : Innovation and Leadership Hub

North America continues to lead the Data Science Platform market, holding a significant share of 70.05% in 2024. The region's growth is driven by rapid technological advancements, increased investment in AI and machine learning, and a strong focus on data-driven decision-making across industries. Regulatory support for innovation and data privacy is also a key catalyst, fostering a conducive environment for market expansion. The competitive landscape is characterized by the presence of major players such as IBM, Microsoft, and Google, which are continuously innovating to enhance their offerings. The U.S. remains the largest market, with Canada and Mexico also contributing to growth. The focus on cloud-based solutions and analytics tools is reshaping the market, making it essential for companies to adapt to evolving consumer demands and regulatory frameworks.

Key Players and Competitive Insights

The Data Science Platform Market is currently characterized by intense competition and rapid innovation, driven by the increasing demand for data-driven decision-making across various industries. Key players such as IBM (US), Microsoft (US), and Google (US) are at the forefront, each adopting distinct strategies to enhance their market presence. IBM (US) focuses on integrating AI capabilities into its platforms, thereby facilitating advanced analytics and machine learning functionalities. Microsoft (US) emphasizes cloud-based solutions, leveraging its Azure platform to provide scalable data science tools. Meanwhile, Google (US) is investing heavily in machine learning and AI, aiming to streamline data processing and enhance user experience through its Google Cloud offerings. Collectively, these strategies not only intensify competition but also foster a dynamic environment where innovation is paramount.

In terms of business tactics, companies are increasingly localizing their operations to better serve regional markets, optimizing supply chains to enhance efficiency. The competitive structure of the Data Science Platform Market appears moderately fragmented, with numerous players vying for market share. However, the influence of major companies is substantial, as they set benchmarks for technology and service delivery, thereby shaping the overall market landscape.

In November 2025, IBM (US) announced a strategic partnership with a leading healthcare provider to develop AI-driven analytics solutions aimed at improving patient outcomes. This collaboration underscores IBM's commitment to leveraging its data science capabilities in the healthcare sector, potentially transforming how data is utilized in clinical settings. The strategic importance of this move lies in its potential to enhance IBM's reputation as a leader in healthcare analytics, while also addressing critical industry needs.

In October 2025, Microsoft (US) launched a new suite of data science tools integrated within its Azure platform, designed to simplify the data analysis process for businesses of all sizes. This initiative reflects Microsoft's ongoing strategy to democratize access to advanced analytics, making it easier for organizations to harness the power of data. The launch is significant as it positions Microsoft as a key player in the growing demand for accessible data science solutions, potentially attracting a broader customer base.

In September 2025, Google (US) unveiled enhancements to its BigQuery platform, incorporating advanced machine learning capabilities that allow users to perform predictive analytics more efficiently. This development is indicative of Google's strategy to maintain its competitive edge by continuously evolving its offerings. The implications of this enhancement are profound, as it not only improves user experience but also solidifies Google's position as a leader in cloud-based data analytics.

As of December 2025, the Data Science Platform Market is witnessing trends such as increased digitalization, a focus on sustainability, and the integration of AI technologies. Strategic alliances among key players are shaping the competitive landscape, fostering innovation and collaboration. Looking ahead, it is likely that competitive differentiation will increasingly hinge on technological advancements and supply chain reliability, rather than solely on price. This shift suggests a future where innovation and the ability to deliver robust, reliable solutions will be the primary drivers of success in the market.

Key Companies in the Data Science Platform Market market include

Industry Developments

  • Q2 2024: Dataiku raises $200M in Series F funding round led by Wellington Management Dataiku, a leading data science platform provider, secured $200 million in Series F funding to accelerate product development and global expansion. The round was led by Wellington Management with participation from existing investors.
  • Q1 2024: Alteryx appoints Mark Anderson as new CEO Alteryx, a prominent data science and analytics platform company, announced the appointment of Mark Anderson as its new Chief Executive Officer, effective immediately.
  • Q2 2024: Databricks acquires Tabular to expand data lakehouse capabilities Databricks, a major player in the data science platform market, acquired Tabular, a startup specializing in data lakehouse technology, to enhance its unified analytics platform.
  • Q1 2024: H2O.ai launches H2O-3 4.0 with enhanced AutoML and explainability features H2O.ai released version 4.0 of its open-source H2O-3 platform, introducing advanced AutoML capabilities and improved model explainability tools for enterprise users.
  • Q2 2024: Snowflake and NVIDIA announce strategic partnership to accelerate AI workloads Snowflake and NVIDIA entered a strategic partnership to integrate NVIDIA's AI computing with Snowflake's data cloud, aiming to streamline AI and data science workflows for enterprise customers.
  • Q1 2024: SAS opens new AI and Data Science Innovation Center in Frankfurt SAS inaugurated a new innovation center in Frankfurt, Germany, dedicated to advancing AI and data science research and supporting European enterprise clients.
  • Q2 2024: RapidMiner acquired by Altair to strengthen data analytics portfolio Altair, a global technology company, completed the acquisition of RapidMiner, a data science platform provider, to bolster its analytics and machine learning offerings.
  • Q1 2024: IBM launches Watsonx, a next-generation data science and AI platform IBM introduced Watsonx, a new platform designed to provide advanced data science, machine learning, and generative AI capabilities for enterprise customers.
  • Q2 2024: DataRobot secures $150M in new funding to fuel AI platform growth DataRobot, a leading AI and data science platform provider, raised $150 million in a new funding round to accelerate product innovation and expand its global footprint.
  • Q1 2024: Oracle announces Oracle Cloud Data Science Platform Market enhancements Oracle unveiled significant enhancements to its Cloud Data Science Platform Market, including new collaboration tools and automated machine learning features for enterprise users.
  • Q2 2024: Microsoft and Databricks deepen partnership with new Azure AI integrations Microsoft and Databricks expanded their partnership by launching new Azure AI integrations, enabling customers to build and deploy advanced machine learning models more efficiently.
  • Q1 2024: Cloudera launches Cloudera Data Science Workbench 3.0 Cloudera released version 3.0 of its Data Science Workbench, featuring improved scalability, security, and support for modern machine learning frameworks.

Future Outlook

Data Science Platform Market Future Outlook

<p>The Data Science Platform Market is projected to grow at a 19.18% CAGR from 2024 to 2035, driven by advancements in AI, big data analytics, and increasing demand for data-driven decision-making.</p>

New opportunities lie in:

  • <p>Development of industry-specific data science solutions for healthcare and finance sectors.</p>
  • <p>Integration of automated machine learning tools to enhance user accessibility.</p>
  • <p>Expansion of cloud-based platforms to facilitate global collaboration and scalability.</p>

<p>By 2035, the Data Science Platform Market is expected to be robust, reflecting substantial growth and innovation.</p>

Market Segmentation

Data Science Platform Market End User Outlook

  • Small and Medium Enterprises
  • Large Enterprises
  • Government Organizations
  • Academic Institutions

Data Science Platform Market Application Outlook

  • Predictive Analytics
  • Data Mining
  • Machine Learning
  • Statistical Analysis
  • Text Analytics

Data Science Platform Market Functionality Outlook

  • Data Preparation
  • Model Building
  • Model Deployment
  • Data Visualization

Data Science Platform Market Deployment Model Outlook

  • On-Premises
  • Cloud-Based
  • Hybrid

Report Scope

MARKET SIZE 2024140.1(USD Billion)
MARKET SIZE 2025163.99(USD Billion)
MARKET SIZE 2035947.97(USD Billion)
COMPOUND ANNUAL GROWTH RATE (CAGR)19.18% (2024 - 2035)
REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
BASE YEAR2024
Market Forecast Period2025 - 2035
Historical Data2019 - 2024
Market Forecast UnitsUSD Billion
Key Companies ProfiledIBM (US), Microsoft (US), Google (US), SAS (US), Oracle (US), SAP (DE), Alteryx (US), DataRobot (US), TIBCO (US), RapidMiner (US)
Segments CoveredApplication, Deployment Model, End User, Functionality
Key Market OpportunitiesIntegration of artificial intelligence and machine learning enhances capabilities in the Data Science Platform Market.
Key Market DynamicsRising demand for advanced analytics drives innovation and competition in the Data Science Platform Market.
Countries CoveredNorth America, Europe, APAC, South America, MEA

FAQs

How much is the Data Science Platform market?

The Data Science Platform market was valued at USD 100.9 Billion in 2022.

What is the growth rate of the Data Science Platform market?

The market is projected to grow at a CAGR of 19.20% from 2023-2030.

Which Region held the largest market share in the Data Science Platform market?

North America had the largest share of the market.

Who are the key players in the Data Science Platform market?

The key players in the market are Microsoft Corporation (U.S.), IBM Corporation (U.S.), Google Inc. (U.S.), and Wolfram (U.S.).

Which Business Function led the Data Science Platform market?

The Sales category dominated the market in 2022.

Which Deployment had the largest market share in the Data Science Platform market?

On-Premises had the most extensive Data Science Platform market share.

  1. Executive Summary
    1. Scope of the Report
    2. Market Definition
      1. Research Objectives
    3. Scope of the Study
    4. Assumptions & Limitations
    5. Markets Structure
  2. Market Research Methodology
    1. Research
    2. Process
    3. Secondary Research
    4. Primary
    5. Research
    6. Forecast Model
  3. Market
    1. Landscape
    2. Porter’s Five Forces Analysis
      1. Bargaining power of buyers
      2. Threat of substitutes
      3. Segment
    3. Threat of New Entrants
    4. rivalry
    5. Value Chain/Supply Chain of Global Data Science
    6. Platform Market
  4. Industry Overview of Global Data Science
    1. Platform Market
    2. Introduction
    3. Growth
    4. Drivers
    5. Impact analysis
    6. Market
    7. Challenges
  5. Market Trends
    1. Introduction
    2. Growth Trends
    3. Impact analysis
  6. Global Data Science Platform Market by Business Type
    1. Introduction
    2. Marketing
      1. Market Estimates
      2. Market Estimates & Forecast by Region,
    3. & Forecast, 2020-2027
    4. Sales
      1. Market Estimates & Forecast,
      2. Market Estimates & Forecast by Region, 2020-2027
      3. Market Estimates & Forecast, 2020-2027
      4. Market Estimates & Forecast by Region, 2020-2027
      5. Market Estimates & Forecast, 2020-2027
      6. Market Estimates & Forecast by Region, 2020-2027
      7. Market Estimates & Forecast, 2020-2027
      8. Market Estimates & Forecast, 2020-2027
      9. Market Estimates & Forecast, 2020-2027
      10. Market Estimates & Forecast, 2020-2027
      11. Market Estimates
    5. Logistics
    6. Human Resources
    7. Operations
    8. Market Estimates & Forecast by Region, 2020-2027
    9. Risk Management
    10. Market Estimates & Forecast by Region, 2020-2027
    11. Customer Support
    12. Market Estimates & Forecast by Region, 2020-2027
    13. Others
    14. & Forecast by Region, 2020-2027
  7. Global Data Science Platform
    1. Market by Deployment
    2. Introduction
      1. Market Estimates & Forecast, 2020-2027
    3. On-Demand
    4. Market Estimates & Forecast by Region, 2020-2027
    5. On-Premise
      1. Market Estimates & Forecast, 2020-2027
      2. Market Estimates &
    6. Forecast by Region, 2020-2027
  8. Global Data Science Platform
    1. Market by Vertical
    2. Introduction
      1. Market Estimates & Forecast, 2020-2027
      2. Market Estimates & Forecast, 2020-2027
      3. Market Estimates
    3. Healthcare
    4. Market Estimates & Forecast by Region, 2020-2027
    5. BFSI
    6. & Forecast by Region, 2020-2027
    7. Defense & government
      1. Market Estimates & Forecast, 2020-2027
      2. Market Estimates &
    8. Forecast by Region, 2020-2027
    9. Retail
      1. Market
      2. Market Estimates & Forecast by
    10. Estimates & Forecast, 2020-2027
    11. Region, 2020-2027
    12. Energy & Utilities
      1. Market Estimates & Forecast
    13. Market Estimates & Forecast, 2020-2027
    14. by Region, 2020-2027
    15. Transportation
      1. Market
      2. Market Estimates & Forecast by
    16. Estimates & Forecast, 2020-2027
    17. Region, 2020-2027
    18. Others
      1. Market Estimates
      2. Market Estimates & Forecast by Region,
    19. & Forecast, 2020-2027
  9. Global Data Science Platform Market
    1. by Region
    2. Introduction
    3. North
      1. Market Estimates & Forecast, 2020-2027
      2. Market
      3. Market Estimates
      4. Market Estimates & Forecast
      5. U.S.
      6. Mexico
    4. America
    5. Estimates & Forecast by Business Type, 2020-2027
    6. & Forecast by Vertical, 2020-2027
    7. by Deployment, 2020-2027
    8. Estimates & Forecast, 2020-2027
    9. by Business Type, 2020-2027
    10. Market Estimates & Forecast by Deployment, 2020-2027
    11. Canada
    12. Market Estimates & Forecast by Business Type, 2020-2027
    13. Estimates & Forecast by Vertical, 2020-2027
    14. Forecast by Deployment, 2020-2027
    15. Europe
      1. Market Estimates & Forecast
      2. Market Estimates & Forecast by Vertical,
      3. Market Estimates & Forecast by Deployment, 2020-2027
      4. Germany
      5. Italy
      6. Spain
    16. Market Estimates & Forecast, 2020-2027
    17. by Business Type, 2020-2027
    18. Market Estimates & Forecast by Deployment, 2020-2027
    19. France
    20. Market Estimates & Forecast by Business Type, 2020-2027
    21. Estimates & Forecast by Vertical, 2020-2027
    22. Forecast by Deployment, 2020-2027
    23. Market Estimates & Forecast, 2020-2027
    24. Forecast by Business Type, 2020-2027
    25. by Vertical, 2020-2027
    26. & Forecast, 2020-2027
    27. Type, 2020-2027
    28. U.K
    29. Market Estimates & Forecast by Business Type, 2020-2027
    30. Estimates & Forecast by Vertical, 2020-2027
    31. Forecast by Deployment, 2020-2027
    32. Asia Pacific
      1. Market Estimates & Forecast, 2020-2027
      2. Market Estimates
      3. Market Estimates & Forecast
      4. Market Estimates & Forecast by Deployment,
      5. China
      6. Japan
      7. Rest of Asia Pacific
      8. Market Estimates & Forecast, 2020-2027
      9. Market Estimates & Forecast by Business Type, 2020-2027
      10. Market Estimates
      11. The Middle East &
      12. Latin Countries
    33. & Forecast by Business Type, 2020-2027
    34. by Vertical, 2020-2027
    35. Forecast, 2020-2027
    36. India
    37. Market Estimates & Forecast by Business Type, 2020-2027
    38. Estimates & Forecast by Vertical, 2020-2027
    39. Forecast by Deployment, 2020-2027
    40. Market Estimates & Forecast, 2020-2027
    41. Forecast by Business Type, 2020-2027
    42. by Vertical, 2020-2027
    43. & Forecast, 2020-2027
    44. Type, 2020-2027
    45. Rest of the world
    46. Market Estimates & Forecast by Vertical, 2020-2027
    47. & Forecast by Deployment, 2020-2027
    48. Africa
    49. Estimates & Forecast by Business Type, 2020-2027
    50. & Forecast by Vertical, 2020-2027
    51. by Deployment, 2020-2027
    52. Estimates & Forecast, 2020-2027
    53. by Business Type, 2020-2027
  10. Company Landscape
  11. Company Profiles
    1. Microsoft
      1. Company Overview
      2. Financial
      3. Key Developments
    2. Corporation (U.S.)
    3. Deployment/Business Segment Overview
    4. Updates
    5. IBM
      1. Company Overview
      2. Financial
      3. Key Developments
    6. Corporation (U.S.)
    7. Deployment/Business Segment Overview
    8. Updates
    9. Google,
      1. Company Overview
      2. Financial
      3. Key Developments
    10. Inc. (U.S.)
    11. Deployment/Business Segment Overview
    12. Updates
    13. Wolfram
      1. Company Overview
      2. Deployment/Business
      3. Financial Updates
    14. (U.S.)
    15. Segment Overview
    16. Key Developments
    17. DataRobot Inc. (U.S.)
      1. Deployment/Business Segment
      2. Financial Updates
    18. Company Overview
    19. Overview
    20. Key Developments
    21. Sense Inc. (U.S.)
      1. Deployment/Business Segment
      2. Financial Updates
    22. Company Overview
    23. Overview
    24. Key Developments
    25. RapidMiner Inc. (U.S.)
      1. Deployment/Business Segment
      2. Financial Updates
    26. Company Overview
    27. Overview
    28. Key Developments
    29. Domino Data Lab (U.S.)
      1. Deployment/Business Segment
      2. Financial Updates
    30. Company Overview
    31. Overview
    32. Key Developments
    33. Dataiku (France)
      1. Deployment/Business Segment
      2. Financial Updates
    34. Company Overview
    35. Overview
    36. Key Developments
    37. Alteryx, Inc. (U.S.)
      1. Deployment/Business Segment
      2. Financial Updates
    38. Company Overview
    39. Overview
    40. Key Developments
  12. Conclusion
    1.  
  13. LIST OF TABLES
  14. Global Data Science
    1. Platform Market: By Region, 2020-2027
  15. North America Data Science
    1. Platform Market: By Country, 2020-2027
  16. Europe Data Science Platform
    1. Market: By Country, 2020-2027
  17. Asia-Pacific Data Science Platform
    1. Market: By Country, 2020-2027
  18. Middle East & Africa Data
    1. Science Platform Market: By Country, 2020-2027
  19. Latin America
    1. Data Science Platform Market: By Country, 2020-2027
  20. Global Data
    1. Science Platform by Business Type Market: By Regions, 2020-2027
    2. Table
  21. North America Data Science Platform by Business Type Market: By Country, 2020-2027
  22. Europe Data Science Platform by Business Type Market: By Country,
    1. Table10 Asia-Pacific Data Science Platform by Business Type
    2. Market: By Country, 2020-2027
    3. Table11 Middle East & Africa Data
    4. Science Platform by Business Type Market: By Country, 2020-2027
    5. Table12
    6. Latin America Data Science Platform by Business Type Market: By Country, 2020-2027
    7. Table13 Global Data Science Platform by Deployment Market: By Regions,
    8. Table14 North America Data Science Platform by Deployment
    9. Market: By Country, 2020-2027
    10. Table15 Europe Data Science Platform by
    11. Deployment Market: By Country, 2020-2027
    12. Table16 Asia-Pacific Data Science
    13. Platform by Deployment Market: By Country, 2020-2027
    14. Table17 Middle
    15. East & Africa Data Science Platform by Deployment Market: By Country, 2020-2027
    16. Table18 Latin America Data Science Platform by Deployment Market: By
    17. Country, 2020-2027
    18. Table19 North America Data Science Platform for Form
    19. Market: By Country, 2020-2027
    20. Table20 Europe Data Science Platform for
    21. Form Market: By Country, 2020-2027
    22. Table21 Asia-Pacific Data Science
    23. Platform for Form Market: By Country, 2020-2027
    24. Table22 Middle East
    25. & Africa Data Science Platform for Form Market: By Country, 2020-2027
    26. Table23 Latin America Data Science Platform for Form Market: By Country, 2020-2027
    27. Table24 Global Business Type Market: By Region, 2020-2027
    28. Table25
  23. North America Data Science Platform Market, By Country
    1. Table26 North
  24. America Data Science Platform Market, By Business Type
    1. Table27 North America
  25. Data Science Platform Market, By Deployment
    1. Table28 North America Data Science
  26. Platform Market, By Vertical
    1. Table29 Europe: Data Science Platform Market,
    2. By Country
  27. Table30 Europe: Data Science Platform Market, By Business
    1. Type
  28. Europe: Data Science Platform Market, By Deployment
    1. Table32
  29. Europe Data Science Platform Market, By Vertical
    1. Table33 Asia-Pacific: Data
  30. Science Platform Market, By Country
    1. Table34 Asia-Pacific: Data
  31. Science Platform Market, By Business Type
  32. Asia-Pacific: Data Science
  33. Platform Market, By Deployment
    1. Table36 Asia-Pacific Data Science Platform Market,
    2. By Vertical
    3. Table37 Middle East & Africa: Data Science Platform Market,
    4. By Country
    5. Table38 Middle East & Africa Data Science Platform Market,
    6. By Business Type
    7. Table39 Middle East & Africa: Data Science Platform
  34. Market, By Deployment
    1. Table40 Middle East & Africa Data Science Platform
  35. Market, By Vertical
    1. Table41 Latin America: Data Science Platform Market,
    2. By Country
  36. Table42 Latin America Data Science Platform Market, By Business
    1. Type
  37. Table43 Latin America: Data Science Platform Market, By Deployment
  38. Table44 Latin America Data Science Platform Market, By Vertical
    1. LIST
  39. OF FIGURES
  40. Global Data Science Platform Market segmentation
  41. Forecast Methodology
  42. Five Forces Analysis of Global Data
    1. Science Platform Market
  43. Value Chain of Global Data Science Platform
    1. Market
  44. Share of Global Data Science Platform Market in 2020,
    1. by country (in %)
  45. Global Data Science Platform Market, 2020-2027,
  46. Sub segments of Business Type
  47. Global Data
    1. Science Platform Market size by Business Type, 2020
  48. Share of
    1. Global Data Science Platform Market by Business Type, 2020 TO 2027
    2. FIGURE 10
    3. Global Data Science Platform Market size by Deployment, 2020 TO 2027
    4. FIGURE
  49. Share of Global Data Science Platform Market by Deployment, 2020 TO 2027
  50. Global Data Science Platform Market size by vertical, 2020 TO
  51. Share of Global Data Science Platform Market by Vertical,

Data Science Platform Market Segmentation

Data Science Platform Business Function Outlook (USD Billion, 2019-2030)

  • Marketing
  • Sales
  • Logistics
  • Human Resources

Data Science Platform Deployment Outlook (USD Billion, 2019-2030)

  • On-Demand
  • On-Premises

Data Science Platform Vertical Outlook (USD Billion, 2019-2030)

  • BFSI
  • Healthcare
  • Retail
  • It
  • Transportation

Data Science Platform Regional Outlook (USD Billion, 2019-2030)

  • North America Outlook (USD Billion, 2019-2030)

    • North America Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • North America Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • North America Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • US Outlook (USD Billion, 2019-2030)

    • US Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • US Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • US Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • CANADA Outlook (USD Billion, 2019-2030)

    • CANADA Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • CANADA Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • CANADA Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

  • Europe Outlook (USD Billion, 2019-2030)

    • Europe Data Science Platform by Business Function
      • Website Classified
      • Social Media Classified
      • Search Engine Marketing
    • Europe Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Europe Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Germany Outlook (USD Billion, 2019-2030)

    • Germany Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Germany Data Science Platform by Deployment
      • On-Demand
      • On-Premises
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • France Outlook (USD Billion, 2019-2030)

    • France Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • France Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • France Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • UK Outlook (USD Billion, 2019-2030)

    • UK Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • UK Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • UK Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • ITALY Outlook (USD Billion, 2019-2030)

    • ITALY Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • ITALY Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • ITALY Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • SPAIN Outlook (USD Billion, 2019-2030)

    • Spain Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Spain Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Spain Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Rest Of Europe Outlook (USD Billion, 2019-2030)

    • Rest Of Europe Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • REST OF EUROPE Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • REST OF EUROPE Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

  • Asia-Pacific Outlook (USD Billion, 2019-2030)

    • Asia-Pacific Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Asia-Pacific Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Asia-Pacific Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • China Outlook (USD Billion, 2019-2030)

    • China Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • China Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • China Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Japan Outlook (USD Billion, 2019-2030)

    • Japan Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Japan Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Japan Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • India Outlook (USD Billion, 2019-2030)

    • India Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • India Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • India Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Australia Outlook (USD Billion, 2019-2030)

    • Australia Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Australia Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Australia Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Rest of Asia-Pacific Outlook (USD Billion, 2019-2030)

    • Rest of Asia-Pacific Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Rest of Asia-Pacific Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Rest of Asia-Pacific Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

  • Rest of the World Outlook (USD Billion, 2019-2030)

    • Rest of the World Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Rest of the World Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Rest of the World Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Middle East Outlook (USD Billion, 2019-2030)

    • Middle East Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Middle East Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Middle East Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Africa Outlook (USD Billion, 2019-2030)

    • Africa Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Africa Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Africa Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation

    • Latin America Outlook (USD Billion, 2019-2030)

    • Latin America Data Science Platform by Business Function
      • Marketing
      • Sales
      • Logistics
      • Human Resources
    • Latin America Data Science Platform by Deployment
      • On-Demand
      • On-Premises
    • Latin America Data Science Platform by Vertical
      • BFSI
      • Healthcare
      • Retail
      • It
      • Transportation
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