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市場調查報告書
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1641936

資料科學平台：市場佔有率分析、產業趨勢與統計、成長預測（2025-2030 年）

Data Science Platform - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 207 Pages | 商品交期: 2-3個工作天內

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簡介目錄

資料科學平台市場規模預計在 2025 年為 125.4 億美元，預計到 2030 年將達到 360.1 億美元，預測期內（2025-2030 年）的複合年成長率為 23.5%。

數據科學平台-市場-IMG1

資料科學的出現為組織提供了解決方案，將資料集轉化為有價值的資源，並透過可操作的見解來增加商業價值。隨著公司和組織數量的指數級成長，資料科學正在成為商業各個方面不可或缺的一部分，並在經營模式中發揮至關重要的作用。

主要亮點

  • 資料科學平台提供了一套工具和服務，使組織能夠管理、存取和分析資料，簡化資料分析流程並擴展他們的資料分析能力。資料科學平台的採用正在成長，因為它具有從預測分析到自動化機器學習過程、做出更明智的決策和更好地利用資料等諸多好處。
  • 公司越來越重視增加內部資料科學資源，以建立機器學習模型並填補稀缺專業人員的招募缺口，從而推動資料科學即服務 (DSaaS) 的興起。對於許多企業來說，DSaaS 已變得至關重要，因為它可以幫助他們擴展分析能力以滿足關鍵需求並推動期望的業務成果。
  • 隨著人工智慧（AI）和機器學習（ML）等技術的快速發展，企業正在接收越來越多的資料，既有資料的，也有基於現有資料集的，而且格式也完全不同。情況就是這樣。因此，為了利用這些資料，公司正在轉向根據其需求量身定做的資料科學解決方案。
  • 缺乏熟練人才造成的一個主要障礙是無法從組織產生的大量資料中獲得有意義的見解。資料科學平台旨在幫助使用者分析和解釋複雜的資料，但缺乏熟練的專家來培訓這些平台會降低其有效性。組織努力彌合其資料科學平台的先進功能與最佳利用這些功能所需的專業知識之間的差距。
  • 新冠疫情加速了商業和工業的數位化，導致對資料主導洞察的需求激增。各行業的組織現在都在使用資料科學來就資源、風險管理和客戶行為做出明智的決策。此外，遠距工作的轉變刺激了雲端基礎的資料科學平台和工具的採用，使資料科學家無論身在何處都能有效協作。這種靈活性和可訪問性對資料科學知識的需求更大。

資料科學平台市場趨勢

小型企業強勁成長

  • 小型企業擁有少於 100 名員工，而中型企業則擁有 100 至 999 名員工。資料科學資料科學在小型企業中的主要用途之一是利用它來追蹤銷售週期各個階段的客戶。小型企業可以使用資料分析來識別可能進行購買的特定消費者群體。資料主導的產業成長是透過基於證據的結論來提高銷售、績效、業務等，從而實現企業永續發展。
  • 小型企業通常資源有限，因此每個決策都很重要。資料科學平台幫助中小型企業做出更明智的決策並降低風險。該平台幫助中小企業識別效率低下的問題並降低業務和供應鏈中的成本。
  • 2023 年 8 月，Infor Nexus 與星展銀行合作宣佈為 Infor Nexus 供應鏈生態系統中的中小型企業 (SME) 供應商推出出貨前融資。該解決方案利用 Infor Nexus 平台的歷史資料來提供基於資料庫的融資解決方案，以幫助滿足供應商營運資金需求。
  • 雲端運算的採用預計將推動市場成長。它徹底改變了中小型企業存取和利用資料科學平台的方式。雲端基礎架構提供可擴展性，允許中小型企業根據其需求的變化無縫地增加或減少資料科學能力。 2023 年 11 月，AnniQ 推出了一項專注於資料分析的新服務，以支援中小企業的策略能力。該服務旨在增強中小企業在業務營運中與資料互動和利用數據的方式，重點提供可操作的見解並推動策略執行。

北美佔據主要市場佔有率

  • 在資料量和複雜性不斷成長的推動下，美國不斷創新其資料科學平台並加強其在全球市場的地位。進階分析、人工智慧（AI）和機器學習（ML）等先進技術的市場引進也對國家經濟產生直接影響。
  • 根據電信諮詢服務公司估計，美國的網路流量將從 2021 年的每月 6,400 萬Exabyte迅速成長到 2023 年的 9,864 萬Exabyte。資料流量的大幅增加需要更先進的資料科學解決方案來管理大量資料並根據提取的資料改進解決方案。此外，組織產生的資料比以往任何時候都多，而且這些資料變得越來越複雜和多樣化。這使得使用傳統方法來分析資料並從中提取見解變得困難。資料科學平台提供管理和分析大型複雜資料庫的工具和基礎設施。
  • 此外，受訪的市場上所有領先供應商都位於美國。此外，該國正處於第四次工業革命的邊緣，資料正在大規模生產中得到利用，同時整合整個供應鏈中不同的製造系統和資料。這導致該國加速採用先進技術。
  • 該地區的政府也採取舉措支持市場上最新技術的發展，促進機器人技術的採用。例如，美國聯邦政府推出了國家機器人計畫（NRI）項目，以加強國內機器人製造能力並鼓勵該領域的研究活動。預計這些舉措將為市場成長帶來積極的前景。
  • 此外，加拿大注重醫療保健、人工智慧和可再生能源等領域的研究和創新，也需要資料科學平台來分析複雜的資料集並獲得研究見解。加拿大的高科技產業正在蓬勃發展，該國熱衷於吸引技術知識。越來越多的行業需要熟練的資料科學家和人工智慧專業人員，包括銀行、醫療保健、金融、保險、媒體和娛樂、電信和電子商務。目前對專家的需求大於現有專家的數量。不斷增強的技術力和對高階 IT 解決方案、AI 和 ML 的需求將推動加拿大資料科學平台市場的發展。

資料科學平台產業概況

資料科學平台市場處於半靜態狀態，產品差異化程度高，產品採用水準不斷提高，技術進步迅速，難以維持競爭優勢，迫使企業持續採用和創新解決方案。主要參與者包括 Alteryx、IBM Corporation、Google LLC（Alphabet Inc.）、SAS、Alteryx 和 Microsoft Corporation。

  • 2023 年 11 月 - IBM 與 Amazon Web Services (AWS) 合作，全面推出適用於 Db2 的 Amazon Relational Database Service (Amazon RDS)。 Amazon RDS 是一種完全託管的雲端服務，旨在讓資料庫客戶更輕鬆地管理混合雲端環境中的人工智慧 (AI) 工作負載的資料。這使客戶能夠利用該公司在 AWS 上的整合資料和 AI 功能來管理他們的資料並擴展他們的 AI 工作負載。
  • 2023 年 8 月 - Google Cloud 和 NVIDIA 擴大夥伴關係，以推進 AI 運算、軟體和服務，幫助客戶建置和部署用於生成式 AI 的大規模模型並加速資料科學工作負載。此次夥伴關係將為全球一些最大的人工智慧客戶提供端到端的機器學習服務，包括讓人工智慧超級電腦在基於 NVIDIA 技術建構的 Google Cloud 產品上輕鬆運作。

其他福利：

  • Excel 格式的市場預測 (ME) 表
  • 3 個月的分析師支持

目錄

第 1 章 簡介

  • 研究假設和市場定義
  • 研究範圍

第2章調查方法

第3章執行摘要

第4章 市場洞察

  • 市場概況
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 消費者議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭對手之間的競爭
  • 宏觀經濟趨勢的影響

第5章 市場動態

  • 市場促進因素
    • 巨量資料的爆炸性成長
    • 資料科學和機器學習的有前景的使用案例的出現
    • 組織向資料密集方法和決策的轉變
  • 市場限制
    • 勞動力缺乏技能
    • 資料安全和信任問題
  • 關鍵使用案例
  • 生態系分析
  • 定價及定價模式分析
  • 資料科學平台的主要功能（人工智慧和機器學習、分析、視覺化、探索、建模）

第6章 市場細分

  • 透過奉獻
    • 平台
    • 服務
  • 按部署
    • 本地
    • 雲
  • 按公司規模
    • 中小企業
    • 大型企業
  • 按行業
    • 資訊科技/通訊
    • BFSI
    • 零售與電子商務
    • 石油、天然氣和能源
    • 製造業
    • 政府和國防
    • 其他行業
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
    • 歐洲
      • 英國
      • 德國
      • 法國
      • 義大利
      • 西班牙
      • 希臘
      • 其他歐洲國家
    • 亞太地區
      • 中國
      • 印度
      • 日本
      • 澳洲
      • 東南亞
      • 印尼
      • 菲律賓
      • 馬來西亞
      • 新加坡
      • 東南亞其他地區
      • 其他亞太地區
    • 拉丁美洲
      • 巴西
      • 阿根廷
      • 墨西哥
      • 其他拉丁美洲國家
    • 中東和非洲
      • 沙烏地阿拉伯
      • GCC
      • 阿拉伯聯合大公國
      • 其他 GCC
      • 南非
      • 其他中東和非洲地區

第7章 競爭格局

  • 公司簡介
    • IBM Corporation
    • Google LLC（Alphabet Inc.）
    • Microsoft Corporation
    • SAS
    • Alteryx
    • The MathWorks Inc.
    • RapidMiner
    • Databricks
    • Amazon Web Services Inc.（AMAZON.COM INC.）
    • DataRobot Inc.

第 8 章廠商市場佔有率分析

第 9 章區域供應商排名

第10章 投資分析

第 11 章：投資分析市場的未來

簡介目錄
Product Code: 62382

The Data Science Platform Market size is estimated at USD 12.54 billion in 2025, and is expected to reach USD 36.01 billion by 2030, at a CAGR of 23.5% during the forecast period (2025-2030).

Data Science Platform - Market - IMG1

Data Science is emerging to provide solutions to organizations to transform data sets into a valuable resource that helps get business value with actionable insights. As the number of business enterprises and organizations grows exponentially, data science is becoming essential in various aspects of business and plays a pivotal role in business models.

Key Highlights

  • The data science platforms offer a suite of tools and services that allow organizations to manage, access, and analyze their data and enable organizations to streamline their data analysis processes and scale their data analysis capabilities. The adoption of data science platforms is growing due to benefits such as predictive analytics to automated machine learning processes, informed decisions, and better utilization of their data.
  • There is an increasing emphasis on businesses boosting their internal data science resources to build machine learning models and fill the hiring gap of in-demand professionals, resulting in increased adoption of data science as a service (DSaaS). For many businesses, it becomes essential as it helps them scale their analytics capabilities to meet critical needs and get the desired outcomes of business.
  • As technologies such as artificial intelligence (AI) and machine learning (ML) are advancing rapidly, businesses are receiving a significantly larger amount of data, including new data based on previously existing datasets and new forms of data altogether. Thus, to use these data, businesses are moving to adopt data science solutions that are compatible with their requirements.
  • One of the primary obstacles arising from the lack of a skilled workforce is the inability to derive meaningful insights from the vast volumes of data organizations generate. Data science platforms are designed to allow users to analyze and interpret complex datasets, but the shortage of skilled professionals capable of guiding these platforms diminishes their effectiveness. Organizations struggle to bridge the gap between the advanced functionalities of data science platforms and the expertise needed to leverage these functionalities optimally.
  • The COVID-19 pandemic accelerated the digitization of businesses and industries, leading to a surge in the need for data-driven insights. Organizations across sectors turned to data science to make informed decisions about resource and risk management and customer behavior. Further, the shift to remote work spurred the adoption of cloud-based data science platforms and tools, enabling data scientists to collaborate effectively from any location. This flexibility and accessibility further fueled the demand for data science expertise.

Data Science Platform Market Trends

Small and Medium Enterprises to Witness Major Growth

  • Small-sized organizations have less than 100 employees, whereas medium-sized enterprises have between 100 to 999 employees. One of the major applications of data science for small businesses is using it to track clients throughout the various stages of the sales cycle. Small businesses can utilize data analytics to determine a particular segment of consumers willing to buy. Data-driven industry growth is making evidence-based conclusions to enhance sales, performance, and operations, among others, through which businesses can achieve sustainable development.
  • SMEs often operate with limited resources, making every decision critical. Data science platforms empower SMEs to make more precise and informed decisions, reducing risks. The platforms help SMEs identify inefficiencies in their operations and supply chains, reducing costs.
  • In August 2023, Infor Nexus and DBS Bank, in partnership, announced the launch of pre-shipment financing for small and medium-sized enterprises (SME) suppliers in the Infor Nexus supply chain ecosystem. This solution utilizes historical data from the Infor Nexus platform to provide data-based lending solutions that help suppliers meet their working capital requirements.
  • Cloud adoption is expected to boost the market's growth. It has revolutionized how SMEs access and utilize data science platforms. Cloud infrastructure offers scalability, allowing SMEs to seamlessly scale their data science capabilities up or down based on their changing needs. In November 2023, AnniQ launched a new service focusing on data analytics to support the strategic capabilities of small and medium-sized enterprises (SMEs). This service is designed to enhance how SMEs engage with and utilize data in their business operations, emphasizing providing actionable insights and facilitating strategic execution.

North America to Hold Significant Market Share

  • Fueled by data's increasing volume and complexity, the United States continues to innovate and consolidate its position in the global market in the data science platforms. The embracing of advanced technologies such as advanced analytics, Artificial Intelligence (AI), and Machine Learning (ML) in the market studied has also directly impacted the national economy.
  • According to Telecom Advisory Services, the estimated Internet traffic in the United States has jumped from 64 million exabytes per month in 2021 to 98.64 million exabytes per month in 2023. Such a significant increase in data traffic needs more advanced data science solutions to manage a large amount of data and improve the solutions based on extracted data. Additionally, organizations are generating more data than ever, which is becoming increasingly complex and diverse. This makes it difficult to analyze and extract insights from data using traditional methods. Data science platforms provide the tools and infrastructure to manage and analyze large and complex databases.
  • Moreover, all the major vendors studied in the market are US-based. Additionally, the country is on the brink of the fourth industrial revolution, where data is being utilized in large-scale production while integrating the data with a wide variety of manufacturing systems throughout the supply chain. This is accelerating the adoption of advanced technologies in the country.
  • The government in the region is also promoting the adoption of robotics by taking initiatives to support the growth of modern technologies in the market. For instance, the US federal government has launched the National Robotics Initiative (NRI) program to strengthen the capabilities of building domestic robots in the nation and encourage research activities in the field. Such initiatives are further expected to create a positive outlook for the market growth.
  • In addition, the strong focus on research and innovation in Canada in sectors like healthcare, artificial intelligence, and renewable energy supports the market requiring data science platforms to analyze complex data sets and gain research insights. Canada's tech industry is flourishing, and the country has made a concerted effort to attract technological know-how. A rising number of sectors, including banking, healthcare, finance, insurance, media and entertainment, telecom, and e-commerce, need qualified Data Scientists and AI experts. Professionals are in greater demand right now than they are available. Expanding technological capabilities and the demand for high-end IT solutions, AI, and ML will drive the market for data science platforms in Canada.

Data Science Platform Industry Overview

The Data Science Platform Market is semi-consolidated and is characterized by high product differentiation, growing levels of product penetration, and rapid advancements in technology, leading to difficulty in maintaining a competitive advantage, forcing them to continuously adopt and innovate solutions. Some of major players include Alteryx, IBM Corporation, Google LLC (Alphabet Inc.), SAS, Alteryx, Microsoft Corporation.

  • November 2023 - IBM collaborated with Amazon Web Services (AWS) on the general availability of Amazon Relational Database Service (Amazon RDS) for Db2, a fully managed cloud offering designed to make it easier for database customers to manage data for artificial intelligence (AI) workloads across hybrid cloud environments. It will allow the users to leverage an array of the company's integrated data and AI capabilities on AWS to manage data and scale AI workloads.
  • August 2023 - Google Cloud and NVIDIA announced a partnership expansion to advance AI computing, software, and services for customers to build and deploy massive models for generative AI and speed data science workloads. The partnership will bring end-to-end machine learning services to some of the largest AI customers in the world - including by making it easy to run AI supercomputers with Google Cloud offerings built on NVIDIA technologies.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitutes
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Impact of Macroeconomic Trends

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Rapid Increase in Big Data
    • 5.1.2 Emerging Promising Use Cases of Data Science and Machine Learning
    • 5.1.3 Shift of Organizations Toward Data-intensive Approach and Decisions
  • 5.2 Market Restraints
    • 5.2.1 Lack of Skillset in Workforce
    • 5.2.2 Data Security and Reliability Concerns
  • 5.3 Key Use Cases
  • 5.4 Ecosystem Analysis
  • 5.5 Analysis of Pricing and Pricing Models
  • 5.6 Key Capabilities of Data Science Platforms (AI & Ml, Analytics, Visualization, Exploration, Modelling)

6 MARKET SEGMENTATION

  • 6.1 By Offering
    • 6.1.1 Platform
    • 6.1.2 Services
  • 6.2 By Deployment
    • 6.2.1 On-premise
    • 6.2.2 Cloud
  • 6.3 By Size of Enterprises
    • 6.3.1 Small and Medium Enterprises
    • 6.3.2 Large Enterprises
  • 6.4 By Industry Vertical
    • 6.4.1 IT and Telecom
    • 6.4.2 BFSI
    • 6.4.3 Retail and E-commerce
    • 6.4.4 Oil Gas and Energy
    • 6.4.5 Manufacturing
    • 6.4.6 Government and Defense
    • 6.4.7 Other Industry Verticals
  • 6.5 By Geography
    • 6.5.1 North America
      • 6.5.1.1 United States
      • 6.5.1.2 Canada
    • 6.5.2 Europe
      • 6.5.2.1 United Kingdom
      • 6.5.2.2 Germany
      • 6.5.2.3 France
      • 6.5.2.4 Italy
      • 6.5.2.5 Spain
      • 6.5.2.6 Greece
      • 6.5.2.7 Rest of Europe
    • 6.5.3 Asia Pacific
      • 6.5.3.1 China
      • 6.5.3.2 India
      • 6.5.3.3 Japan
      • 6.5.3.4 Australia
      • 6.5.3.5 Southeast Asia
      • 6.5.3.5.1 Indonesia
      • 6.5.3.5.2 Philippines
      • 6.5.3.5.3 Malaysia
      • 6.5.3.5.4 Singapore
      • 6.5.3.5.5 Rest of Southeast Asia
      • 6.5.3.6 Rest of Asia Pacific
    • 6.5.4 Latin America
      • 6.5.4.1 Brazil
      • 6.5.4.2 Argentina
      • 6.5.4.3 Mexico
      • 6.5.4.4 Rest of Latin America
    • 6.5.5 Middle East and Africa
      • 6.5.5.1 Saudi Arabia
      • 6.5.5.2 GCC
      • 6.5.5.2.1 United Arab Emirates
      • 6.5.5.2.2 Rest of GCC
      • 6.5.5.3 South Africa
      • 6.5.5.4 Rest of Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 IBM Corporation
    • 7.1.2 Google LLC (Alphabet Inc.)
    • 7.1.3 Microsoft Corporation
    • 7.1.4 SAS
    • 7.1.5 Alteryx
    • 7.1.6 The MathWorks Inc.
    • 7.1.7 RapidMiner
    • 7.1.8 Databricks
    • 7.1.9 Amazon Web Services Inc. (AMAZON.COM INC.)
    • 7.1.10 DataRobot Inc.

8 VENDOR SHARE ANALYSIS

9 RANKING OF VENDORS AT A REGIONAL LEVEL

10 INVESTMENT ANALYSIS

11 FUTURE OF THE MARKET