한글목차

자율 데이터 플랫폼 세계 시장 규모는 2024년에 18억 7,000만 달러로 평가되었습니다. 2030년에는 72억 1,000만 달러에 달하고, 예측 기간 중 연평균 복합 성장률(CAGR)은 25.22%를 보일 것으로 예측됩니다.

이 시장에는 인공지능, 머신러닝, 고급 분석 등의 기술을 활용하여 인간의 개입을 최소화하는 지능형 자체 운영 데이터 관리 시스템이 포함됩니다. 이러한 플랫폼은 수집, 통합, 저장, 거버넌스, 분석 등 엔드투엔드 데이터 기능을 자동으로 관리합니다. 이를 통해 기업은 데이터 성능을 개선하고, 컴플라이언스를 유지하며, 적시에 통찰력을 제공함으로써 복잡한 디지털 생태계에서 중요한 역할을 할 수 있도록 설계되어 있습니다. 산업 전반에 걸쳐 생성되는 데이터 양 증가와 실시간 분석 및 오류 없는 업무에 대한 수요 증가가 자율형 데이터 플랫폼의 도입을 촉진하는 주요 요인으로 작용하고 있습니다. 헬스케어, 금융, 소매, 제조 등 다양한 분야의 조직들이 비용 절감, 정확도 향상, 대규모 디지털 전환을 지원하기 위해 이러한 플랫폼을 도입하고 있습니다.

시장 성장 촉진요인

기업의 디지털 전환을 위한 노력 가속화

주요 시장 이슈

높은 구현 복잡성 및 통합 장벽

주요 시장 동향

산업 특화형 자율 데이터 솔루션 확대

목차

제1장 솔루션 개요

• 시장의 정의
• 시장 범위
  • 대상 시장
  • 조사 대상년
  • 주요 시장 세분화

제2장 조사 방법

제3장 주요 요약

제4장 고객의 소리

제5장 세계의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
  • 금액별
• 시장 점유율과 예측
  • 컴포넌트별(플랫폼, 서비스)
  • 전개 형태별(On-Premise, 클라우드)
  • 업계별(은행/금융서비스/보험(BFSI), 소매, 헬스케어, IT 및 통신, 제조, 정부, 기타)
  • 지역별(북미, 유럽, 남미, 중동 및 아프리카, 아시아태평양)
• 기업별(2024년)
• 시장 맵

제6장 북미의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
• 시장 점유율과 예측
• 북미 : 국가별 분석
  • 미국
  • 캐나다
  • 멕시코

제7장 유럽의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
• 시장 점유율과 예측
• 유럽 : 국가별 분석
  • 독일
  • 프랑스
  • 영국 자율형 데이터 플랫폼 시장
  • 이탈리아
  • 스페인

제8장 아시아태평양의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
• 시장 점유율과 예측
• 아시아태평양 : 국가별 분석
  • 중국
  • 인도
  • 일본
  • 한국
  • 호주

제9장 중동 및 아프리카의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
• 시장 점유율과 예측
• 중동 및 아프리카 : 국가별 분석
  • 사우디아라비아
  • 아랍에미리트(UAE)
  • 남아프리카공화국

제10장 남미의 자율 데이터 플랫폼 시장 전망

• 시장 규모와 예측
• 시장 점유율과 예측
• 남미 : 국가별 분석
  • 브라질
  • 콜롬비아
  • 아르헨티나

제11장 시장 역학

• 성장 촉진요인
• 과제

제12장 시장 동향과 발전

• 인수합병(M&A)
• 제품 출시
• 최근 동향

제13장 기업 개요

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

제14장 전략적 제안

제15장 회사 소개 및 면책조항

영문목차

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