查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
2030 年資料科學平台市場預測：按部署模式、組件、組織規模、用途、最終用戶和區域進行的全球分析
市場調查報告書
商品編碼
1359005

2030 年資料科學平台市場預測：按部署模式、組件、組織規模、用途、最終用戶和區域進行的全球分析

Data Science Platform Market Forecasts to 2030 - Global Analysis By Deployment Mode, Component, Organization Size, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，2023 年全球資料科學平台市場規模為 1,505.7 億美元，預計到 2030 年將達到 7,466.3 億美元，預測期內年複合成長率為 25.7%。

資料科學平台是所有資料科學和資料分析活動的中心樞紐。資料科學平台提供專案生命週期每個階段所需的所有工具，包括構思、設定、發現、模型開發和軟體實作。資料科學家可以利用資料科學平台更快地執行、追蹤、複製、分析和共用他們的工作。資料科學平台就是企業廣泛使用的軟體工具之一。

據儲存解決方案提供商 Seagate 稱，到 2025 年，全球創建的資料量將增加到 175 ZB。

巨量資料的使用迅速增加

隨著社群媒體、物聯網和其他媒體的發展，專業人士捕獲的資料量不斷擴大。資料科學平台正在產生大量的結構化和非結構化資料。一般來說，基於機器的資料和人類產生的資料的成長是傳統企業資料的10倍，而機器資料的產生速度快50倍。資料提供的巨大成長為企業提供了獲取新數據的機會，從而導致對新方法的需求不斷成長，並在推動資料科學平台市場方面發揮關鍵作用。

缺乏技術熟練程度

在當今的商業環境中經常使用流分析、機器學習和預測分析等高級分析技術。然而，這些技術很困難，因為它們需要先進的分析能力。例如，創建機器學習模型需要技術專業知識、分析能力和批判性思考能力。不幸的是，許多最終用戶缺乏知識淵博且技術熟練的員工。因此，缺乏技術知識和訓練有素的人力資源預計將在不久的將來成為資料科學平台市場的主要挑戰。

巨額投資和技術進步

據估計，研發方面的高投資將創造利潤豐厚的市場機會，並加速資料科學平台市場的成長。此外，人工智慧（AI）、機器學習（ML）和物聯網（IoT）等技術的快速發展為市場提供了廣泛的成長機會。

業務問題的不確定性

公司必須使用資料科學平台對他們想要解決的問題進行廣泛的研究。如果您不了解當前的業務問題，那麼簡單地選擇資料並執行資料分析是沒有效率的。使用資料科學平台做出資訊的決策的效率明顯較低。此外，如果對實施資料科學平台的期望與目標不一致，那麼即使目標明確，公司的努力也可能無效。在整個預期期間，這項特殊要素預計將帶來一系列抑製成長的挑戰。

COVID-19 的影響：

COVID-19將對市場擴張產生積極影響，並在整個預測期內提供豐富的擴張機會。這些機會包括資料應用的成長、企業對資料科學平台的需求以及尖端資料科學平台解決方案的推出。由於全面停擺，組織被迫走向數位化，為員工設立在家工作的負責人。由於 COVID-19 大流行，隨著主要科技公司將自動化和智慧整合到其組織中，人們對資料科學平台的興趣增加。

預計本地部門將成為預測期內最大的細分市場

預計本地細分市場的市場規模在預測期內將會增加。在經常線上上存取的遠端電腦網路上管理、處理和儲存資料的做法稱為雲端運算。企業主要在 BFSI、醫療保健、生命科學和製造等高度法規的領域中利用資料科學平台的本地部署策略。此外，擁有充足IT資源的大型企業預計將選擇本地部署方式，加速市場成長。

大型企業領域預計在預測期內年複合成長率最高

預計大型企業部門在預測期內將出現良好的成長。大公司一般是指員工人數在1000人以上的公司。由於雲端的日益普及，許多大型企業正在利用資料科學平台，而這一趨勢預計將持續下去。大公司從不同的基本客群收集大量資料。在大型企業中，資料對於確定整個組織的績效至關重要。由於上述因素，預計該領域將出現成長。

佔比最大的地區：

預計北美在預測期內將佔據最大的市場佔有率。各行業的主要企業正在向該地區擴張，預計這將加速市場擴張。此外，對最尖端科技的投資增加正在推動對產品的需求。由於主要市場參與者的存在，該地區的收入佔有率正在增加。此外，美國和加拿大持續投資於可以使用資料來支援業務決策的尖端解決方案。該地區的公司正在利用技術進行創新和擴大市場。

複合年複合成長率最高的地區：

預計亞太地區在預測期內將出現快速成長。巨量資料分析工具的採用預計將在各行業中迅速增加。鑑於資料分析工具的用途和使用案例眾多，中國、韓國和印度等政府也正在投資這些工具。此外，由於行動數據流量增加導致資料數量和複雜性急劇增加，以及業務營運中新的物聯網和人工智慧應用程式的增加，該地區各行業在其經濟中的巨量資料技術支出將增加也因為這樣的要素不斷成長，這給市場帶來了很多機會。

提供免費客製化

訂閱此報告的客戶將收到以下免費自訂選項之一：

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 家公司）
    • 主要企業SWOT分析（最多3家企業）
  • 區域分割
    • 根據客戶興趣對主要國家的市場估計、預測和年複合成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章 執行摘要

第2章 前言

  • 概述
  • 利害關係人
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 資料分析
    • 資料檢驗
    • 研究途徑
  • 調查來源
    • 主要調查來源
    • 二次調查來源
    • 先決條件

第3章 市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 最終用戶分析
  • 新型冠狀病毒感染疾病（COVID-19）的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第5章 全球資料科學平台市場：依部署模式

  • 雲
  • 本地

第6章 全球資料科學平台市場：按組成部分

  • 諮詢
  • 部署與整合
  • 平台
  • 支援與維護
  • 服務
    • 專業的服務
    • 管理服務

第7章 全球資料科學平台市場：依組織規模

  • 中小企業
  • 主要企業

第8章 全球資料科學平台市場：依用途

  • 客戶支援
  • 財會
  • 人力資源和營運
  • 後勤
  • 行銷
  • 銷售
  • 其他用途

第9章 全球資料科學平台市場：依最終用戶分類

  • 銀行、金融服務和保險 (BFSI)
  • 能源和公用事業
  • 政府和國防
  • 醫療保健和生命科學
  • 資訊科技和通訊
  • 製造業
  • 媒體和娛樂
  • 零售與電子商務
  • 運輸和物流
  • 其他最終用戶

第10章 全球資料科學平台市場：按地區

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲

第11章進展

  • 合約、夥伴關係、協作和合資企業
  • 收購和合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第12章公司簡介

  • Altair Inc.
  • Alteryx Inc.
  • Amazon Web Services, Inc.
  • Anaconda Inc.
  • Apheris AI GmbH
  • Arrikto Inc.
  • Cloudera Inc.
  • Databand
  • Databricks
  • Dataiku
  • DataRobot Inc.
  • Domino Data Lab Inc.
  • Explorium Inc.
  • Google Inc
  • H2O.ai
  • IBM Corporation
  • Iterative
  • MathWorks, Inc.
  • Microsoft Corporation
  • Oracle Corporation
  • RapidMiner
  • SAP SE
  • Teradata
Product Code: SMRC23877

According to Stratistics MRC, the Global Data Science Platform Market is accounted for $150.57 billion in 2023 and is expected to reach $746.63 billion by 2030 growing at a CAGR of 25.7% during the forecast period. Data science platform serves as a central hub for all data science and data analysis activities. The data science platform provides all the tools necessary for every stage of a project's life cycle, including ideation, setup, discovery, model development, and software implementation. Data scientists can more quickly run, track, replicate, analyze, and share their work due to the data science platform. The data science platform is one such software tool that is widely used by businesses.

According to Seagate, the storage solutions provider, the volume of data created worldwide will grow to 175 ZB by 2025.

Market Dynamics:

Driver:

Soaring use of big data

As there is growth in social media, IOT, and other media, the amount of data that professionals capture is constantly expanding. A massive flow of structured and unstructured data has been produced by data science platforms. In general, the growth of machine-based and human-generated data is 10 times greater than that of traditional corporate data, and the rate at which machine data is produced is 50 times faster. The enormous growth in data offerings provides opportunities for businesses to acquire new things, which led to a rise in demand for novel approaches and plays a critical role in driving the market for data science platforms.

Restraint:

Lack of technical proficiency

Advanced analytics techniques like streaming analytics, machine learning, and predictive analytics are frequently used in the current business environment. These techniques do, however, pose difficulties because they call for a high level of analytical proficiency. For instance, creating a machine learning model requires technical expertise, analytical prowess, and critical thinking skills. Unfortunately, many end users do not have staff members who are knowledgeable and skilled. Therefore, it is anticipated that the lack of technical know-how and trained personnel will pose a significant challenge for the market for data science platforms in the near future.

Opportunity:

High investment and technological advancements

According to estimates, the substantial investment in research and development will create profitable market opportunities and accelerate the growth of the data science platform market. Further, the market is presented with a wide range of growth opportunities due to the quick development of technologies like artificial intelligence (AI), machine learning (ML), and the internet of things (IoT).

Threat:

Uncertainty regarding the business issues

Businesses must do extensive research on the problems they want to use a data science platform to solve. Simply selecting datasets and performing data analysis can have low productivity if the business problem at hand is not understood. Making informed decisions using a data science platform is significantly less effective. A company's efforts may also be ineffective even if it has a clearly defined goal in mind if its expectations for the implementation of a data science platform do not match its goals. Throughout the anticipated period, it is anticipated that this particular factor will produce a number of growth-impeding challenges.

COVID-19 Impact:

The COVID-19 had a favorable impact on market expansion and will offer an abundance of opportunity for expansion throughout the forecast period. These opportunities include the rise in data applications, the demand for data science platforms in enterprises, and the introduction of cutting-edge data science platform solutions. Organizations were forced to move toward digitalization in order to set up work-from-home officers for their employees due to the general lockdown. As the major technology companies integrate automation and intelligence into their organizations as a result of the COVID-19 pandemic, this is driving interest in data science platforms.

The On-premises segment is expected to be the largest during the forecast period

Over the projection period, it is predicted that the on-premises segment will experience a larger market size. The practice of managing, processing, and storing data over networks of distant computers that are frequently accessed online is known as cloud computing. Businesses primarily use the data science platform's on-premises deployment strategy in highly regulated sector verticals like BFSI, healthcare and life sciences, and manufacturing. Additionally, it is anticipated that large businesses with sufficient IT resources will select the on-premises deployment approach, which is accelerating market growth.

The large enterprises segment is expected to have the highest CAGR during the forecast period

During the forecast period, it is expected that the large enterprises segment will experience lucrative growth. Large companies are generally defined as those with more than or equal to 1,000 employees. Numerous large companies are utilizing the data science platform as a result of the cloud's rising popularity, and this trend is anticipated to continue. Massive amounts of data are gathered by large companies from their diverse customer bases. In large businesses, data is essential for determining how well an organization is performing overall. The aforementioned elements are expected to cause the segment to grow.

Region with largest share:

Over the forecast period, North America is anticipated to dominate the largest market share. Key players from a variety of industries are present in this region, which is anticipated to accelerate market expansion. Additionally, rising investments in cutting-edge technologies are driving up product demand. The region's revenue share is increased by the presence of major market players there. Furthermore, the United States and Canada are consistently investing in a cutting-edge solution that can use data to aid in business decision-making. Companies in the area are utilizing technology to innovate and expand their markets.

Region with highest CAGR:

During the forecast period, a rapid growth rate is anticipated in the Asia-Pacific region. It is expected that the adoption of big data analytics tools will increase quickly across industries. In light of the numerous applications and use cases for data analytics tools, the governments of China, South Korea, India, and other countries are also making investments in these tools. Additionally, the industry in this region is also growing as a result of factors like increased spending on big data technologies in economies due to the rapid rise in the volume and complexity of numbers as a result of the increase in mobile data traffic and new IoT and AI applications in business operations, which are opening up a lot of opportunities for the market.

Key players in the market:

Some of the key players in Data Science Platform Market include: Altair Inc., Alteryx Inc., Amazon Web Services, Inc., Anaconda Inc., Apheris AI GmbH, Arrikto Inc., Cloudera Inc., Databand, Databricks, Dataiku, DataRobot Inc., Domino Data Lab Inc., Explorium Inc., Google Inc, H2O.ai, IBM Corporation, Iterative, MathWorks, Inc., Microsoft Corporation, Oracle Corporation, RapidMiner, SAP SE and Teradata.

Key Developments:

In September 2023, Anaconda is excited to announce the public release of Anaconda Assistant, an AI-powered Jupiter notebook extension designed to enhance the productivity of data scientists, developers, and researchers. Anaconda Assistant is now available to all users of Anaconda cloud notebooks. Powered by the same large language model behind ChatGPT, the Assistant provides an intuitive chat interface to help generate, explain, or debug code, learn new topics, and more.

In August 2023, Altair, a global leader in computational science and artificial intelligence (AI), announced that Lydonia Technologies, the leading provider of hyperautomation software and solutions, has joined its growing channel partner network. Lydonia Technologies will offer Altair® RapidMiner® - Altair's data analytics and AI platform - as well as Altair SLC™, an alternative SAS language environment, to customers in the U.S. Specializing in hyperautomation services and solutions, Lydonia Technologies helps companies increase the automation of their business processes through AI, machine learning, and robotic process automation (RPA).

In August 2023, Alteryx, Inc. the Analytics Cloud Platform company, is expanding its partnership with Google Cloud to provide Looker Studio users with native access to a free limited version of Alteryx Designer Cloud's AI-powered data preparation capabilities and enhanced connectivity. This new integration builds on Alteryx and Google Cloud's commitment to make it easier for customers to surface critical insights for decision-makers in a timely manner, resulting in actions that can improve business outcomes.

Deployment Modes Covered:

  • Cloud
  • On-premises

Components Covered:

  • Consulting
  • Deployment and Integration
  • Platform
  • Support and Maintenance
  • Services

Organization Sizes Covered:

  • Small and Medium-Sized Enterprises
  • Large Enterprises

Applications Covered:

  • Customer Support
  • Finance and Accounting
  • Human Resources and Operations
  • Logistics
  • Marketing
  • Sales
  • Other Applications

End Users Covered:

  • Banking, Financial Services and Insurance (BFSI)
  • Energy and Utilities
  • Government and Defense
  • Healthcare and Life Sciences
  • Information Technology and Telecommunication
  • Manufacturing
  • Media and Entertainment
  • Retail and e-Commerce
  • Transportation and Logistics
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Data Science Platform Market, By Deployment Mode

  • 5.1 Introduction
  • 5.2 Cloud
  • 5.3 On-premises

6 Global Data Science Platform Market, By Component

  • 6.1 Introduction
  • 6.2 Consulting
  • 6.3 Deployment and Integration
  • 6.4 Platform
  • 6.5 Support and Maintenance
  • 6.6 Services
    • 6.6.1 Professional Services
    • 6.6.2 Managed Services

7 Global Data Science Platform Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Small and Medium-Sized Enterprises
  • 7.3 Large Enterprises

8 Global Data Science Platform Market, By Application

  • 8.1 Introduction
  • 8.2 Customer Support
  • 8.3 Finance and Accounting
  • 8.4 Human Resources and Operations
  • 8.5 Logistics
  • 8.6 Marketing
  • 8.7 Sales
  • 8.8 Other Applications

9 Global Data Science Platform Market, By End User

  • 9.1 Introduction
  • 9.2 Banking, Financial Services and Insurance (BFSI)
  • 9.3 Energy and Utilities
  • 9.4 Government and Defense
  • 9.5 Healthcare and Life Sciences
  • 9.6 Information Technology and Telecommunication
  • 9.7 Manufacturing
  • 9.8 Media and Entertainment
  • 9.9 Retail and e-Commerce
  • 9.10 Transportation and Logistics
  • 9.11 Other End Users

10 Global Data Science Platform Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Altair Inc.
  • 12.2 Alteryx Inc.
  • 12.3 Amazon Web Services, Inc.
  • 12.4 Anaconda Inc.
  • 12.5 Apheris AI GmbH
  • 12.6 Arrikto Inc.
  • 12.7 Cloudera Inc.
  • 12.8 Databand
  • 12.9 Databricks
  • 12.10 Dataiku
  • 12.11 DataRobot Inc.
  • 12.12 Domino Data Lab Inc.
  • 12.13 Explorium Inc.
  • 12.14 Google Inc
  • 12.15 H2O.ai
  • 12.16 IBM Corporation
  • 12.17 Iterative
  • 12.18 MathWorks, Inc.
  • 12.19 Microsoft Corporation
  • 12.20 Oracle Corporation
  • 12.21 RapidMiner
  • 12.22 SAP SE
  • 12.23 Teradata

List of Tables

  • Table 1 Global Data Science Platform Market Outlook, By Region (2021-2030) ($MN)
  • Table 2 Global Data Science Platform Market Outlook, By Deployment Mode (2021-2030) ($MN)
  • Table 3 Global Data Science Platform Market Outlook, By Cloud (2021-2030) ($MN)
  • Table 4 Global Data Science Platform Market Outlook, By On-premises (2021-2030) ($MN)
  • Table 5 Global Data Science Platform Market Outlook, By Component (2021-2030) ($MN)
  • Table 6 Global Data Science Platform Market Outlook, By Consulting (2021-2030) ($MN)
  • Table 7 Global Data Science Platform Market Outlook, By Deployment and Integration (2021-2030) ($MN)
  • Table 8 Global Data Science Platform Market Outlook, By Platform (2021-2030) ($MN)
  • Table 9 Global Data Science Platform Market Outlook, By Support and Maintenance (2021-2030) ($MN)
  • Table 10 Global Data Science Platform Market Outlook, By Services (2021-2030) ($MN)
  • Table 11 Global Data Science Platform Market Outlook, By Professional Services (2021-2030) ($MN)
  • Table 12 Global Data Science Platform Market Outlook, By Managed Services (2021-2030) ($MN)
  • Table 13 Global Data Science Platform Market Outlook, By Organization Size (2021-2030) ($MN)
  • Table 14 Global Data Science Platform Market Outlook, By Small and Medium-Sized Enterprises (2021-2030) ($MN)
  • Table 15 Global Data Science Platform Market Outlook, By Large Enterprises (2021-2030) ($MN)
  • Table 16 Global Data Science Platform Market Outlook, By Application (2021-2030) ($MN)
  • Table 17 Global Data Science Platform Market Outlook, By Customer Support (2021-2030) ($MN)
  • Table 18 Global Data Science Platform Market Outlook, By Finance and Accounting (2021-2030) ($MN)
  • Table 19 Global Data Science Platform Market Outlook, By Human Resources and Operations (2021-2030) ($MN)
  • Table 20 Global Data Science Platform Market Outlook, By Logistics (2021-2030) ($MN)
  • Table 21 Global Data Science Platform Market Outlook, By Marketing (2021-2030) ($MN)
  • Table 22 Global Data Science Platform Market Outlook, By Sales (2021-2030) ($MN)
  • Table 23 Global Data Science Platform Market Outlook, By Other Applications (2021-2030) ($MN)
  • Table 24 Global Data Science Platform Market Outlook, By End User (2021-2030) ($MN)
  • Table 25 Global Data Science Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2021-2030) ($MN)
  • Table 26 Global Data Science Platform Market Outlook, By Energy and Utilities (2021-2030) ($MN)
  • Table 27 Global Data Science Platform Market Outlook, By Government and Defense (2021-2030) ($MN)
  • Table 28 Global Data Science Platform Market Outlook, By Healthcare and Life Sciences (2021-2030) ($MN)
  • Table 29 Global Data Science Platform Market Outlook, By Information Technology and Telecommunication (2021-2030) ($MN)
  • Table 30 Global Data Science Platform Market Outlook, By Manufacturing (2021-2030) ($MN)
  • Table 31 Global Data Science Platform Market Outlook, By Media and Entertainment (2021-2030) ($MN)
  • Table 32 Global Data Science Platform Market Outlook, By Retail and e-Commerce (2021-2030) ($MN)
  • Table 33 Global Data Science Platform Market Outlook, By Transportation and Logistics (2021-2030) ($MN)
  • Table 34 Global Data Science Platform Market Outlook, By Other End Users (2021-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.