自律データプラットフォーム市場- 世界の産業規模、シェア、動向、機会、予測、業界別、展開別、地域別、競合別2020-2030年

自律データプラットフォームの世界市場規模は、2024年に18億7,000万米ドルで、2030年には72億1,000万米ドルに達すると予測され、予測期間中のCAGRは25.22%で成長すると予測されています。

この市場には、人工知能、機械学習、高度分析などの技術を活用することで、人間の介入を最小限に抑えるインテリジェントな自己運用型データ管理システムが含まれます。これらのプラットフォームは、収集、統合、保管、ガバナンス、分析など、エンドツーエンドのデータ機能を自動的に管理します。その設計により、企業はデータパフォーマンスの向上、コンプライアンスの維持、タイムリーな洞察の提供が可能になり、複雑なデジタルエコシステムにおいて重要な役割を果たします。業界全体で生成されるデータ量の増加と、リアルタイムのアナリティクスとエラーのない業務に対する需要の高まりが、自律型データプラットフォームの採用を促進する主な要因となっています。ヘルスケア、金融、小売、製造など、さまざまな分野の組織が、コスト削減、精度向上、大規模なデジタルトランスフォーメーションの支援のために、これらのプラットフォームを導入しています。

市場促進要因

企業のデジタルトランスフォーメーションへの取り組みの加速

主な市場課題

高い実装の複雑性と統合の障壁

主な市場動向

業界特化型自律データソリューションの拡大

目次

第1章 ソリューションの概要

• 市場の定義
• 市場の範囲
  • 対象市場
  • 調査対象年
  • 主要市場セグメンテーション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 顧客の声

第5章 世界の自律データプラットフォーム市場展望

• 市場規模・予測
  • 金額別
• 市場シェア・予測
  • コンポーネント別（プラットフォーム、サービス）
  • 展開別（オンプレミス、クラウド）
  • 業界別（BFSI、小売、ヘルスケア、IT・通信、製造、政府、その他）
  • 地域別（北米、欧州、南米、中東・アフリカ、アジア太平洋）
• 企業別（2024）
• 市場マップ

第6章 北米の自律データプラットフォーム市場展望

• 市場規模と予測
• 市場シェア・予測
• 北米：国別分析
  • 米国
  • カナダ
  • メキシコ

第7章 欧州の自律データプラットフォーム市場展望

• 市場規模と予測
• 市場シェア・予測
• 欧州：国別分析
  • ドイツ
  • フランス
  • 英国の自律型データプラットフォーム市場
  • イタリア
  • スペイン

第8章 アジア太平洋地域の自律データプラットフォーム市場展望

• 市場規模と予測
• 市場シェアと予測
• アジア太平洋：国別分析
  • 中国
  • インド
  • 日本
  • 韓国
  • オーストラリア

第9章 中東・アフリカの自律データプラットフォーム市場展望

• 市場規模と予測
• 市場シェアと予測
• 中東・アフリカ：国別分析
  • サウジアラビア
  • アラブ首長国連邦
  • 南アフリカ

第10章 南米の自律データプラットフォーム市場展望

• 市場規模・予測
• 市場シェア・予測
• 南米：国別分析
  • ブラジル
  • コロンビア
  • アルゼンチン

第11章 市場力学

• 促進要因
• 課題

第12章 市場動向と発展

• 合併と買収
• 製品上市
• 最近の動向

第13章 企業プロファイル

• IBM Corporation
• MicrosoftCorporation
• SAP SE
• Salesforce, Inc.
• Snowflake Inc.
• Oracle Corporation
• HCL Technologies Limited
• Teradata Corporation
• Cloudera, Inc.

第14章 戦略的提言

第15章 調査会社について・免責事項

The Global Autonomous Data Platform Market was valued at USD 1.87 billion in 2024 and is anticipated to reach USD 7.21 billion by 2030, growing at a CAGR of 25.22% during the forecast period. This market encompasses intelligent, self-operating data management systems that minimize human intervention by leveraging technologies such as artificial intelligence, machine learning, and advanced analytics. These platforms manage end-to-end data functions-including collection, integration, storage, governance, and analysis-automatically. Their design enables enterprises to enhance data performance, maintain compliance, and deliver timely insights, thereby playing a crucial role in complex digital ecosystems. The rising data volumes generated across industries, combined with a growing demand for real-time analytics and error-free operations, are key factors fueling the adoption of autonomous data platforms. Organizations across sectors such as healthcare, finance, retail, and manufacturing are implementing these platforms to reduce costs, improve accuracy, and support digital transformation at scale.

Key Market Drivers

Accelerating Enterprise Digital Transformation Initiatives

Digital transformation is a central strategy across modern enterprises, and autonomous data platforms are increasingly seen as essential enablers of this shift. These platforms automate the complete data lifecycle-from ingestion to analysis-requiring minimal manual oversight, which aligns with the digital-first approaches adopted across industries. As organizations focus on agility and innovation, autonomous platforms offer the scalability and intelligence needed to support smart, connected ecosystems. The United Nations Digital Economy Report highlights that over 65% of the global GDP in 2023 was digitally influenced, indicating how integral data-driven platforms have become in driving business performance and competitiveness.

With the expansion of digital infrastructure, the complexity of managing large, diverse datasets has grown. Autonomous data platforms simplify integration across legacy and modern systems, streamline real-time decision-making, and facilitate cross-functional collaboration. This reduces the burden on data engineers and allows technical teams to focus on innovation. As a result, these platforms are helping organizations build adaptive, intelligent frameworks that enhance operational agility and deliver faster business outcomes.

Key Market Challenges

High Implementation Complexity and Integration Barriers

Despite their advantages, deploying autonomous data platforms presents significant challenges, particularly related to integration and implementation within existing enterprise environments. Many organizations continue to rely on legacy infrastructures that are not optimized for the automated, self-managing capabilities offered by modern platforms. These outdated systems often include fragmented data warehouses, manual governance protocols, and on-premises setups with limited cloud compatibility.

Migrating to an autonomous platform typically requires comprehensive reengineering of core data architecture, updates to data pipelines, and alignment of internal workflows. This transformation demands significant financial investment and technical resources, which can extend deployment timelines and disrupt ongoing operations. The complexity and scale of integration efforts act as major barriers to adoption, especially for organizations seeking seamless and minimally disruptive transitions. As a result, implementation remains a critical challenge, despite the strong business case for automation and intelligence in data management.

Key Market Trends

Expansion of Industry-Specific Autonomous Data Solutions

The market is witnessing a growing shift toward customized autonomous data platforms tailored to the specific requirements of different industries. Rather than offering generalized capabilities, vendors are introducing specialized solutions designed to meet sectoral compliance standards, data structures, and performance needs. Industries such as healthcare, finance, retail, and manufacturing are seeing increasing adoption of domain-focused platforms that deliver improved insights and operational alignment.

For example, in healthcare, platforms are being developed with features that manage protected health information and support compliance with regulations like HIPAA, while enabling predictive clinical analytics. Financial institutions are adopting platforms that offer real-time fraud detection and risk analytics aligned with regulatory mandates. These industry-specific platforms streamline deployment, enhance ROI, and meet strategic business goals more effectively. The move toward verticalized offerings allows vendors to differentiate their products and meet rising demand for tailored, high-performance data management solutions.

Key Market Players

• IBM Corporation
• Microsoft Corporation
• SAP SE
• Salesforce, Inc.
• Snowflake Inc.
• Oracle Corporation
• HCL Technologies Limited
• Teradata Corporation
• Cloudera, Inc.

Report Scope:

In this report, the Global Autonomous Data Platform Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Autonomous Data Platform Market, By Component:

• Platform
• Services

Autonomous Data Platform Market, By Deployment:

• On-premises
• Cloud

Autonomous Data Platform Market, By Vertical:

• BFSI
• Retail
• Healthcare
• IT & Telecom
• Manufacturing
• Government
• Others

Autonomous Data Platform Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa
• South America
  • Brazil
  • Colombia
  • Argentina

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Autonomous Data Platform Market.

Available Customizations:

Global Autonomous Data Platform Market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Solution Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. BaselineMethodology
• 2.3. Key IndustryPartners
• 2.4. Major Association and Secondary Sources
• 2.5. ForecastingMethodology
• 2.6. Data Triangulation& Validation
• 2.7. Assumptions andLimitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Autonomous Data Platform Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Platform,Services)
  • 5.2.2. By Deployment(On-premises, Cloud)
  • 5.2.3. By Vertical (BFSI,Retail, Healthcare, IT & Telecom, Manufacturing, Government, Others)
  • 5.2.4. By Region (North America, Europe, South America,Middle East & Africa, Asia Pacific)
• 5.3. By Company (2024)
• 5.4. Market Map

6. North America Autonomous Data Platform Market Outlook

• 6.1. Market Size &Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component
  • 6.2.2. By Deployment
  • 6.2.3. By Vertical
  • 6.2.4. By Country
• 6.3. North America:Country Analysis
  • 6.3.1. United States Autonomous Data Platform Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1.By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1.By Component
      • 6.3.1.2.2.By Deployment
      • 6.3.1.2.3.By Vertical
  • 6.3.2. Canada Autonomous Data Platform Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1.By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1.By Component
      • 6.3.2.2.2.By Deployment
      • 6.3.2.2.3.By Vertical
  • 6.3.3. Mexico Autonomous Data Platform Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1.By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1.By Component
      • 6.3.3.2.2.By Deployment
      • 6.3.3.2.3.By Vertical

7. Europe Autonomous Data Platform Market Outlook

• 7.1. Market Size &Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Deployment
  • 7.2.3. By Vertical
  • 7.2.4. By Country
• 7.3. Europe: CountryAnalysis
  • 7.3.1. Germany Autonomous Data Platform Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1.By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1.By Component
      • 7.3.1.2.2.By Deployment
      • 7.3.1.2.3.By Vertical
  • 7.3.2. France Autonomous Data Platform Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1.By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1.By Component
      • 7.3.2.2.2.By Deployment
      • 7.3.2.2.3.By Vertical
  • 7.3.3. United Kingdom Autonomous DataPlatform Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1.By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1.By Component
      • 7.3.3.2.2.By Deployment
      • 7.3.3.2.3.By Vertical
  • 7.3.4. Italy Autonomous Data Platform Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1.By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1.By Component
      • 7.3.4.2.2.By Deployment
      • 7.3.4.2.3.By Vertical
  • 7.3.5. Spain Autonomous Data Platform Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1.By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1.By Component
      • 7.3.5.2.2.By Deployment
      • 7.3.5.2.3.By Vertical

8. Asia Pacific Autonomous Data Platform Market Outlook

• 8.1. Market Size &Forecast
  • 8.1.1. By Value
• 8.2. Market Share &Forecast
  • 8.2.1. By Component
  • 8.2.2. By Deployment
  • 8.2.3. By Vertical
  • 8.2.4. By Country
• 8.3. Asia Pacific:Country Analysis
  • 8.3.1. China Autonomous Data Platform Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1.By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1.By Component
      • 8.3.1.2.2.By Deployment
      • 8.3.1.2.3.By Vertical
  • 8.3.2. India Autonomous Data Platform Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1.By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1.By Component
      • 8.3.2.2.2.By Deployment
      • 8.3.2.2.3.By Vertical
  • 8.3.3. Japan Autonomous Data Platform Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1.By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1.By Component
      • 8.3.3.2.2.By Deployment
      • 8.3.3.2.3.By Vertical
  • 8.3.4. South Korea Autonomous Data Platform Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1.By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1.By Component
      • 8.3.4.2.2.By Deployment
      • 8.3.4.2.3.By Vertical
  • 8.3.5. Australia Autonomous Data Platform Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1.By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1.By Component
      • 8.3.5.2.2.By Deployment
      • 8.3.5.2.3.By Vertical

9. Middle East & Africa Autonomous Data Platform Market Outlook

• 9.1. Market Size &Forecast
  • 9.1.1. By Value
• 9.2. Market Share &Forecast
  • 9.2.1. By Component
  • 9.2.2. By Deployment
  • 9.2.3. By Vertical
  • 9.2.4. By Country
• 9.3. Middle East &Africa: Country Analysis
  • 9.3.1. Saudi Arabia Autonomous Data Platform Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1.By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1.By Component
      • 9.3.1.2.2.By Deployment
      • 9.3.1.2.3.By Vertical
  • 9.3.2. UAE Autonomous Data Platform Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1.By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1.By Component
      • 9.3.2.2.2.By Deployment
      • 9.3.2.2.3.By Vertical
  • 9.3.3. South Africa Autonomous Data Platform Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1.By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1.By Component
      • 9.3.3.2.2.By Deployment
      • 9.3.3.2.3.By Vertical

10. South America Autonomous Data Platform Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Deployment
  • 10.2.3. By Vertical
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Autonomous Data Platform Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Deployment
      • 10.3.1.2.3. By Vertical
  • 10.3.2. Colombia Autonomous Data Platform Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Deployment
      • 10.3.2.2.3. By Vertical
  • 10.3.3. Argentina Autonomous Data Platform Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Deployment
      • 10.3.3.2.3. By Vertical

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends and Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Company Profiles

• 13.1. IBM Corporation
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services Offered
• 13.2. MicrosoftCorporation
• 13.3. SAP SE
• 13.4. Salesforce, Inc.
• 13.5. Snowflake Inc.
• 13.6. Oracle Corporation
• 13.7. HCL Technologies Limited
• 13.8. Teradata Corporation
• 13.9. Cloudera, Inc.

14. Strategic Recommendations

15. About Us & Disclaimer