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市場調查報告書

商品編碼

1620609

自主資料平台市場機會、成長動力、產業趨勢分析與 2024 年至 2032 年預測

Autonomous Data Platform Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2024 to 2032

出版日期: 2024年10月22日 | 出版商:

Global Market Insights Inc. | 英文 170 Pages | 商品交期: 2-3個工作天內

價格

簡介目錄

2023 年，全球自主資料平台市場資料為 16 億美元，預計 2024 年至 2032 年複合年成長率為 22.7%。推動的隨著企業擴大處理大量複雜資料。傳統的資料管理方法通常在速度、準確性和可擴展性方面存在不足，這使得人工智慧驅動的平台對於現代組織至關重要。人工智慧和機器學習為自主資料平台帶來了自動化和進階分析，減少了手動干預的需要，並顯著提高了營運效率。這些技術還支援預測分析，幫助企業預測趨勢並做出更明智、主動的決策。

這對於醫療保健、金融和零售等行業尤其有利，及時、準確的資料洞察可以提供競爭優勢。在應用方面，資料分析領域預計到 2023 年將佔據 44% 的市場佔有率，預計到 2032 年將超過 35 億美元。隨著組織產生大量資料，自主平台旨在簡化分析流程，使企業能夠以最少的手動工作提取有價值的見解，從而提高效率和決策。在資料資料，平台細分市場將在 2023 年以資料 % 的佔有率佔據主導地位。功能。

這種統一的方法減少了對多個不同系統的需求，從而簡化了資料管理並提高了整體營運效率。美國在市場上處於領先地位，到2023 年將佔據72% 的市場佔有率，預計到2032 年將達到18 億美元。公司、新創公司和企業研究機構。矽谷等創新中心處於人工智慧、機器學習和資料分析進步的前沿，推動了各行各業自主資料平台的快速開發和採用。這種環境加速了技術進步並促進了資料管理領域尖端解決方案的採用。

市場範圍
開始年份	2023年
預測年份	2024-2032
起始值	16 億美元
預測值	100 億美元
複合年成長率	22.7%

產業生態系統分析
- 技術提供者
- 人工智慧和機器學習提供者
- 數據整合商
- 最終用戶
供應商格局
利潤率分析
技術與創新格局
專利分析
自主資料平台的用例
自主資料平台案例研究
重要新聞和舉措
監管環境
衝擊力
- 成長動力
  - 資料生成指數成長
  - 資料管理解決方案中人工智慧和機器學習解決方案的不斷整合
  - 日益關注資料治理和合規性
  - 越來越重視數據驅動的決策
- 產業陷阱與挑戰
  - 數據品質問題平台與工具
  - 與現有遺留系統的整合挑戰
成長潛力分析
波特的分析
PESTEL分析

第 4 章：競爭格局

介紹
公司市佔率分析
競爭定位矩陣
戰略展望矩陣

第 5 章：市場估計與預測：按組成部分，2021 - 2032 年

主要趨勢
平台
服務
- 諮詢
- 一體化
- 支援與維護

第 6 章：市場估計與預測：按部署模型，2021 - 2032 年

主要趨勢
本地
雲

第 7 章：市場估計與預測：依組織規模，2021 - 2032 年

主要趨勢
中小企業
大型企業

第 8 章：市場估計與預測：依應用分類，2021 - 2032

主要趨勢
數據整合
數據分析
資料治理

第 9 章：市場估計與預測：依最終用途，2021 - 2032 年

主要趨勢
BFSI
衛生保健
零售
製造業
資訊科技和電信
政府
其他

第 10 章：市場估計與預測：按地區，2021 - 2032

主要趨勢
北美洲
- 美國
- 加拿大
歐洲
- 英國
- 德國
- 法國
- 西班牙
- 義大利
- 北歐人
- 俄羅斯
亞太地區
- 中國
- 印度
- 日本
- 韓國
- 澳新銀行
- 東南亞
拉丁美洲
- 巴西
- 墨西哥
- 阿根廷
MEA
- 阿拉伯聯合大公國
- 南非
- 沙烏地阿拉伯

第 11 章：公司簡介

Alteryx
Ataccama
Amazon
Cloudera
Collibra
DataRobot
Denodo
Dremio
DvSum
Gemini Data
HPE (MapR)
IBM
Informatica
Oracle Corporation
QlikTech International AB
Qubole
Salesforce
Sisense
Teradata
Zaloni

簡介目錄

Product Code: 11934

The Global Autonomous Data Platform Market was valued at USD 1.6 billion in 2023 and is forecasted to grow at a CAGR of 22.7% from 2024 to 2032. This growth is largely driven by the rising use of AI and machine learning (ML) in data management as businesses increasingly deal with vast volumes of complex data. Traditional data management methods often fall short in terms of speed, accuracy, and scalability, making AI-driven platforms essential for modern organizations. AI and ML bring automation and advanced analytics to autonomous data platforms, reducing the need for manual intervention and significantly enhancing operational efficiency. These technologies also enable predictive analytics, helping businesses anticipate trends and make more informed, proactive decisions.

This is particularly beneficial for industries such as healthcare, finance, and retail, where timely and accurate data insights can provide a competitive edge. In terms of application, the data analytics segment estimated 44% of the market share in 2023 and is projected to surpass USD 3.5 billion by 2032. This segment's growth is fueled by the increasing reliance on data-driven decision-making across industries. With organizations generating vast amounts of data, autonomous platforms are designed to streamline the analytics process, enabling businesses to extract valuable insights with minimal manual effort, thereby improving efficiency and decision-making. When it comes to components, the platform segment dominated the market with a 73% share in 2023. Autonomous data platforms play a critical role in automating various data processes, and the platform component integrates essential functions like data integration, storage, processing, and analytics.

This unified approach simplifies data management and enhances overall operational efficiency by reducing the need for multiple disparate systems. The U.S. led the market, holding 72% of the market share in 2023, is expected to reach USD 1.8 billion by 2032. The country's dominance is attributed to its robust tech ecosystem, which includes a high concentration of leading technology companies, startups, and research institutions. Innovation hubs such as Silicon Valley are at the forefront of AI, ML, and data analytics advancements, driving the rapid development and adoption of autonomous data platforms across a wide range of industries. This environment accelerates technological progress and fosters the adoption of cutting-edge solutions in data management.

Market Scope
Start Year	2023
Forecast Year	2024-2032
Start Value	$1.6 Billion
Forecast Value	$10 Billion
CAGR	22.7%

Chapter 1 Methodology & Scope

1.1 Research design
- 1.1.1 Research approach
- 1.1.2 Data collection methods
1.2 Base estimates and calculations
- 1.2.1 Base year calculation
- 1.2.2 Key trends for market estimates
1.3 Forecast model
1.4 Primary research & validation
- 1.4.1 Primary sources
- 1.4.2 Data mining sources
1.5 Market definitions

Chapter 2 Executive Summary

2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
- 3.1.1 Technology providers
- 3.1.2 AI and ML providers
- 3.1.3 Data integrators
- 3.1.4 End users
3.2 Supplier landscape
3.3 Profit margin analysis
3.4 Technology & innovation landscape
3.5 Patent analysis
3.6 Use cases of autonomous data platform
3.7 Case studies of autonomous data platform
3.8 Key news & initiatives
3.9 Regulatory landscape
3.10 Impact forces
- 3.10.1 Growth drivers
  - 3.10.1.1 Exponential growth in data generation
  - 3.10.1.2 Growing integration of AI and ML solutions in data management solutions
  - 3.10.1.3 Increasing focus on data governance and compliance
  - 3.10.1.4 Rising emphasis on data-driven decision making
- 3.10.2 Industry pitfalls & challenges
  - 3.10.2.1 Data quality issues the platforms and tools
  - 3.10.2.2 Integration challenges with existing legacy systems
3.11 Growth potential analysis
3.12 Porter's analysis
3.13 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

4.1 Introduction
4.2 Company market share analysis
4.3 Competitive positioning matrix
4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2032 ($Bn)

5.1 Key trends
5.2 Platform
5.3 Services
- 5.3.1 Advisory
- 5.3.2 Integration
- 5.3.3 Support & maintenance

Chapter 6 Market Estimates & Forecast, By Deployment Model, 2021 - 2032 ($Bn)

6.1 Key trends
6.2 On-premises
6.3 Cloud

Chapter 7 Market Estimates & Forecast, By Organization Size, 2021 - 2032 ($Bn)

7.1 Key trends
7.2 SME
7.3 Large enterprises

Chapter 8 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)

8.1 Key trends
8.2 Data integration
8.3 Data analytics
8.4 Data governance

Chapter 9 Market Estimates & Forecast, By End Use, 2021 - 2032 ($Bn)

9.1 Key trends
9.2 BFSI
9.3 Healthcare
9.4 Retail
9.5 Manufacturing
9.6 IT and telecom
9.7 Government
9.8 Others

Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2032 ($Bn)

10.1 Key trends
10.2 North America
- 10.2.1 U.S.
- 10.2.2 Canada
10.3 Europe
- 10.3.1 UK
- 10.3.2 Germany
- 10.3.3 France
- 10.3.4 Spain
- 10.3.5 Italy
- 10.3.6 Nordics
- 10.3.7 Russia
10.4 Asia Pacific
- 10.4.1 China
- 10.4.2 India
- 10.4.3 Japan
- 10.4.4 South Korea
- 10.4.5 ANZ
- 10.4.6 Southeast Asia
10.5 Latin America
- 10.5.1 Brazil
- 10.5.2 Mexico
- 10.5.3 Argentina
10.6 MEA
- 10.6.1 UAE
- 10.6.2 South Africa
- 10.6.3 Saudi Arabia