세계의 DataOps 시장 예측(-2032년) : 구성요소별, 전개 방식별, 기업 규모별, 운영 모델별, 용도별, 최종사용자별, 지역별 분석

According to Stratistics MRC, the Global DataOps Market is accounted for $6.79 billion in 2025 and is expected to reach $29.95 billion by 2032 growing at a CAGR of 23.6% during the forecast period. DataOps is an automated, process-oriented methodology that improves the quality, speed, and reliability of data analytics. It integrates data engineering, data management, and operations to streamline data pipelines from ingestion to delivery. By using automation, agile practices, collaboration, and continuous monitoring, DataOps ensures faster insights and reduces errors. It helps organizations manage complex, large-scale datasets efficiently while maintaining governance, security, and consistency.

Market Dynamics:

Driver:

Rising demand for real-time data analytics & AI

DataOps platforms are enabling continuous integration and delivery of data, which is crucial for high-velocity analytics environments. Companies are relying on automation and orchestration tools to eliminate manual bottlenecks and accelerate insights. The rise of IoT devices and streaming data sources is further intensifying the demand for agile data processing. This strong alignment between operational analytics and AI adoption is significantly boosting the DataOps market.

Restraint:

Shortage of skilled data professionals

Many organizations struggle to implement advanced pipelines because they lack expertise in automation, cloud-native tools, and distributed architectures. Training cycles for DataOps professionals are long, which slows adoption timelines. Companies are turning to managed services and low-code platforms to overcome talent gaps, but these solutions cannot fully replace specialized skills. The deficit in multi-disciplinary capabilities spanning data management, DevOps, and analytics continues to hinder scalability. As a result, talent shortages remain one of the biggest barriers to DataOps expansion.

Opportunity:

Rise of data mesh and decentralized architectures

The data models enable domain-driven data ownership, reducing bottlenecks associated with centralized systems. Organizations are adopting federated governance frameworks to improve transparency and scalability across data ecosystems. DataOps tools are evolving to support self-service data products and cross-domain collaboration. This shift is fostering innovation and enabling enterprises to modernize legacy infrastructures. As decentralized architectures gain momentum, DataOps adoption is expected to accelerate significantly.

Threat:

Data security and privacy concerns

High levels of data movement across pipelines expose organizations to greater privacy risks. Regulatory frameworks such as GDPR and national data protection acts demand strict controls that can complicate DataOps workflows. Companies must invest in encryption, access controls, and automated compliance monitoring to safeguard sensitive information. Misconfigured pipelines and insufficient governance can lead to costly violations and reputational damage. Increasing data security breaches pose a significant threat to the adoption of DataOps practices.

Covid-19 Impact:

The Covid-19 pandemic accelerated digital transformation and intensified the need for automated data workflows. Many organizations adopted cloud-native DataOps tools to support remote operations and distributed teams. Supply chain disruptions increased reliance on real-time analytics, elevating the importance of agile data management. Companies invested in collaborative platforms to maintain data quality and operational continuity during lockdowns. The crisis also highlighted gaps in data governance, prompting stronger adoption of standardized frameworks.

The software segment is expected to be the largest during the forecast period

The software segment is expected to account for the largest market share during the forecast period, due to its central role in pipeline automation and orchestration. Organizations are adopting advanced platforms that integrate governance, monitoring, and data quality in a unified environment. Modern DataOps software supports cloud migration, containerization, and continuous data delivery, which enhances operational efficiency. Vendors are incorporating AI-driven capabilities to optimize workload management and pipeline performance. The shift toward real-time analytics platforms further strengthens software uptake.

The healthcare providers segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare providers segment is predicted to witness the highest growth rate, due to rising demand for real-time clinical and operational insights. Hospitals are leveraging DataOps to improve patient outcomes by streamlining data flows across disparate systems. The expansion of telemedicine and remote diagnostics is creating new data integration challenges that DataOps can solve. Healthcare organizations are adopting automated pipelines to strengthen compliance with regulatory frameworks and ensure data accuracy. AI-powered decision support systems are further driving the need for scalable DataOps solutions.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to its advanced digital infrastructure and strong enterprise adoption. The region benefits from the presence of leading cloud, analytics, and automation technology providers. Organizations in the U.S. and Canada are early adopters of AI-driven data platforms, accelerating DataOps penetration. Investments in big data modernization and large-scale cloud migration further strengthen demand. Regulatory emphasis on data governance encourages companies to implement robust DataOps frameworks.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, owing to rapid digitalization across emerging economies. Enterprises are increasingly investing in cloud-native analytics and modern data infrastructures. Growing adoption of AI, IoT, and automation technologies is driving demand for efficient DataOps practices. Countries such as China, India, and Singapore are strengthening data governance policies that support structured data management. Expanding startup ecosystems and government digital initiatives are further fueling market growth.

Key players in the market

Some of the key players in DataOps Market include Microsoft, IBM, Amazon Web, Google, Oracle, Collibra, Informatica, Hitachi Va, Databricks, Dataiku, Snowflake, DataKitche, Alteryx, Teradata, and Talend.

Key Developments:

In November 2025, IBM and the University of Dayton announced an agreement for the joint research and development of next-generation semiconductor technologies and materials. The collaboration aims to advance critical technologies for the age of AI including AI hardware, advanced packaging, and photonics.

In October 2025, Oracle announced collaboration with Microsoft to develop an integration blueprint to help manufacturers improve supply chain efficiency and responsiveness. The blueprint will enable organizations using Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) to improve data-driven decision making and automate key supply chain processes by capturing live insights from factory equipment and sensors through Azure IoT Operations and Microsoft Fabric.

Components Covered:

• Software
• Services
• Other Components

Deployment Modes Covered:

• Cloud
• On-Premises

Enterprise Sizes Covered:

• Large Enterprises
• Small and Medium Enterprises (SMEs)

Operating Models Covered:

• DevOps
• Agile Development
• Lean Manufacturing

Applications Covered:

• Data Integration and ETL
• Pipeline Orchestration
• Data Quality and Observability
• Data Governance / Compliance
• Real-time Analytics
• MLOps and AI Workflow Integration
• Business Intelligence

End Users Covered:

• Banking, Financial Services, and Insurance (BFSI)
• IT and Telecommunications
• Manufacturing
• Retail and E-commerce
• Healthcare & Life Sciences
• Government and Public Sector
• Energy and Utilities

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 2024, 2025, 2026, 2028, and 2032
• 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 Emerging Markets
• 3.9 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 DataOps Market, By Component

• 5.1 Introduction
• 5.2 Software
  • 5.2.1 Data Integration and ETL Tools
  • 5.2.2 Data Analytics Platforms
  • 5.2.3 Data Quality Tools
  • 5.2.4 Collaboration and Workflow Management
  • 5.2.5 Data Governance Solutions
  • 5.2.6 Data Pipeline Automation/Orchestration Tools
  • 5.2.7 Data Visualization Tools
  • 5.2.8 Metadata Management Solutions
• 5.3 Services
  • 5.3.1 Consulting Services
  • 5.3.2 Deployment and Integration Services
  • 5.3.3 Training, Support, and Maintenance Services
• 5.4 Other Components

6 Global DataOps Market, By Deployment Mode

• 6.1 Introduction
• 6.2 Cloud
  • 6.2.1 Public Cloud
  • 6.2.2 Private Cloud
  • 6.2.3 Hybrid Cloud
• 6.3 On-Premises

7 Global DataOps Market, By Enterprise Size

• 7.1 Introduction
• 7.2 Large Enterprises
• 7.3 Small and Medium Enterprises (SMEs)

8 Global DataOps Market, By Operating Model

• 8.1 Introduction
• 8.2 DevOps
• 8.3 Agile Development
• 8.4 Lean Manufacturing

9 Global DataOps Market, By Application

• 9.1 Introduction
• 9.2 Data Integration and ETL
• 9.3 Pipeline Orchestration
• 9.4 Data Quality and Observability
• 9.5 Data Governance / Compliance
• 9.6 Real-time Analytics
• 9.7 MLOps and AI Workflow Integration
• 9.8 Business Intelligence

10 Global DataOps Market, By End User

• 10.1 Introduction
• 10.2 Banking, Financial Services, and Insurance (BFSI)
• 10.3 IT and Telecommunications
• 10.4 Manufacturing
• 10.5 Retail and E-commerce
• 10.6 Healthcare & Life Sciences
• 10.7 Government and Public Sector
• 10.8 Energy and Utilities

11 Global DataOps Market, By Geography

• 11.1 Introduction
• 11.2 North America
  • 11.2.1 US
  • 11.2.2 Canada
  • 11.2.3 Mexico
• 11.3 Europe
  • 11.3.1 Germany
  • 11.3.2 UK
  • 11.3.3 Italy
  • 11.3.4 France
  • 11.3.5 Spain
  • 11.3.6 Rest of Europe
• 11.4 Asia Pacific
  • 11.4.1 Japan
  • 11.4.2 China
  • 11.4.3 India
  • 11.4.4 Australia
  • 11.4.5 New Zealand
  • 11.4.6 South Korea
  • 11.4.7 Rest of Asia Pacific
• 11.5 South America
  • 11.5.1 Argentina
  • 11.5.2 Brazil
  • 11.5.3 Chile
  • 11.5.4 Rest of South America
• 11.6 Middle East & Africa
  • 11.6.1 Saudi Arabia
  • 11.6.2 UAE
  • 11.6.3 Qatar
  • 11.6.4 South Africa
  • 11.6.5 Rest of Middle East & Africa

12 Key Developments

• 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 12.2 Acquisitions & Mergers
• 12.3 New Product Launch
• 12.4 Expansions
• 12.5 Other Key Strategies

13 Company Profiling

• 13.1 Microsoft
• 13.2 IBM
• 13.3 Amazon Web Services
• 13.4 Google
• 13.5 Oracle
• 13.6 Collibra
• 13.7 Informatica
• 13.8 Hitachi Vantara
• 13.9 Databricks
• 13.10 Dataiku
• 13.11 Snowflake
• 13.12 DataKitchen
• 13.13 Alteryx
• 13.14 Teradata
• 13.15 Talend