基于云端的水分析市场－全球产业规模、份额、趋势、机会和预测，按组件、按部署模式、按应用、按地区和竞争细分，2020-2030 年

2024 年全球基于云端的水分析市场价值为 184.3 亿美元，预计到 2030 年将达到 353.7 亿美元，复合年增长率为 11.48%。基于云端的水分析是指使用云端运算平台即时收集、分析和管理与水相关的资料，以进行监测、最佳化和预测洞察。

这些平台利用感测器、物联网设备、人工智慧演算法和巨量资料分析来追踪水质、用水量、分配、洩漏和环境影响。透过集中存取关键水资料，基于云端的系统可协助公用事业、产业和政府增强决策能力，优化资源利用，并满足法规合规性。与传统的水管理系统不同，基于云端的分析技术具有可扩展性、远端存取、更低的基础设施成本以及与智慧城市框架的无缝整合。

由于全球水资源短缺日益加剧、基础设施老化以及严格的环境法规推动公用事业和各行各业寻求更智慧的解决方案，基于云端的水资源分析市场正在蓬勃发展。城镇化和工业化加剧了水资源压力，高效的监测和管理至关重要。此外，洪水、干旱和污染爆发等气候变迁事件凸显了预测性水资源分析的需求。作为智慧城市计画的一部分，政府和市政当局正在大力投资数位水资源解决方案，而各行各业也需要能够改善资产管理和提高营运效率的工具。人工智慧、机器学习和物联网技术与云端平台的集成，透过实现预测性维护、洩漏检测和即时警报，进一步增强了其价值主张。

全球云端水分析市场的未来成长将受到云端运算技术的进步、智慧型装置的普及以及「监控即服务」(MaaS) 商业模式日益普及的推动。由于订阅模式降低了前期成本，即使是小型公用事业公司和新兴经济体也能使用先进的水分析工具。技术提供者、水务公司和政府之间的合作正在促进创新并扩大市场覆盖范围。由于快速的城市化和水资源管理挑战，亚太地区正逐渐成为高成长地区，全球市场可望持续成长。总体而言，对高效、智慧且合规的水管理系统的需求将在未来几年推动云端分析技术的普及。

关键市场驱动因素

全球水资源短缺加剧，高效率资源管理需求上升

主要市场挑战

与传统基础设施和现有水管理系统的集成

主要市场趋势

人工智慧和机器学习在水分析的应用

目录

第 1 章：解决方案概述

• 市场定义
• 市场范围
  • 覆盖市场
  • 考虑学习的年限
  • 主要市场区隔

第二章：研究方法

第三章：执行摘要

第四章：顾客之声

第五章：全球云端水分析市场展望

• 市场规模和预测
  • 按价值
• 市场占有率和预测
  • 按组件（解决方案、服务）
  • 依部署模式（公共云端、私有云端、混合云端）
  • 依应用（水质监测、洩漏侦测与管理、资产管理、需求预测与消费分析、洪水监测与灾害管理、法规遵循与报告、废水处理分析）
  • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
• 按公司分类（2024）
• 市场地图

第六章：北美云端水分析市场展望

• 市场规模和预测
• 市场占有率和预测
• 北美：国家分析
  • 美国
  • 加拿大
  • 墨西哥

第七章：欧洲云端水分析市场展望

• 市场规模和预测
• 市场占有率和预测
• 欧洲：国家分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太地区云端水分析市场展望

• 市场规模和预测
• 市场占有率和预测
• 亚太地区：国家分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

第九章：中东和非洲云端水分析市场展望

• 市场规模和预测
• 市场占有率和预测
• 中东和非洲：国家分析
  • 沙乌地阿拉伯
  • 阿联酋
  • 南非

第十章：南美洲云端水分析市场展望

• 市场规模和预测
• 市场占有率和预测
• 南美洲：国家分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第 11 章：市场动态

• 驱动程式
• 挑战

第 12 章：市场趋势与发展

• 合併与收购（如有）
• 产品发布（如有）
• 最新动态

第十三章：公司简介

• ABB Ltd.
• General Electric Company
• IBM Corporation
• Microsoft Corporation
• Schneider Electric SE
• Siemens AG
• Oracle Corporation
• Suez SA

第 14 章：策略建议

第15章调查会社について・免责事项

Global Cloud-based Water Analytics Market was valued at USD 18.43 Billion in 2024 and is expected to reach USD 35.37 Billion by 2030 with a CAGR of 11.48% through 2030. Cloud-based water analytics refers to the use of cloud computing platforms to collect, analyze, and manage water-related data in real time for monitoring, optimization, and predictive insights.

These platforms leverage sensors, IoT devices, AI algorithms, and big data analytics to track water quality, usage, distribution, leakages, and environmental impacts. By enabling centralized access to critical water data, cloud-based systems help utilities, industries, and governments enhance decision-making, optimize resource usage, and meet regulatory compliance. Unlike traditional water management systems, cloud-based analytics offer scalability, remote access, lower infrastructure costs, and seamless integration with smart city frameworks.

The market for cloud-based water analytics is rising due to increasing global water scarcity, aging infrastructure, and stringent environmental regulations pushing utilities and industries toward smarter solutions. Urbanization and industrialization have intensified pressure on water resources, making efficient monitoring and management essential. Furthermore, climate change-driven events like floods, droughts, and contamination outbreaks highlight the need for predictive water analytics. Governments and municipalities are investing heavily in digital water solutions as part of smart city projects, while industries demand tools for better asset management and operational efficiency. The integration of AI, machine learning, and IoT technologies into cloud platforms further enhances their value proposition by enabling predictive maintenance, leakage detection, and real-time alerts.

The future growth of the global cloud-based water analytics market will be propelled by advancements in cloud computing, the proliferation of smart devices, and the increasing adoption of Monitoring-as-a-Service (MaaS) business models. As subscription-based models reduce upfront costs, even small utilities and emerging economies can access advanced water analytics tools. Partnerships between technology providers, water utilities, and governments are fostering innovation and expanding market reach. With Asia Pacific emerging as a high-growth region due to its rapid urbanization and water management challenges, the market is poised for sustained growth globally. Overall, the demand for efficient, intelligent, and compliant water management systems will drive the adoption of cloud-based analytics in the years ahead.

Key Market Drivers

Rising Global Water Scarcity and Demand for Efficient Resource Management

The increasing scarcity of freshwater resources is compelling governments, industries, and utilities worldwide to seek advanced solutions for monitoring and managing water usage. Population growth, rapid urbanization, and climate change have collectively stressed global water supplies. Cloud-based water analytics platforms allow organizations to track consumption patterns, detect inefficiencies, and optimize distribution systems in real time. These platforms support sustainable water management by enabling data-driven decisions, predictive maintenance, and leakage detection-functions critical to minimizing wastage and ensuring equitable distribution.

For instance, agriculture accounts for approximately 70% of global freshwater withdrawals according to the Food and Agriculture Organization (FAO). Cloud-based analytics help optimize irrigation systems by analyzing water needs based on soil moisture data, weather forecasts, and historical usage patterns. Similarly, urban utilities leverage real-time analytics to identify leakages-responsible for up to 30% of water loss in distribution networks-and take timely corrective action. By integrating cloud platforms with IoT-enabled sensors, utilities and industrial users gain actionable insights, which support both operational efficiency and environmental sustainability. By 2025, an estimated 1.8 billion people will live in regions suffering from absolute water scarcity, as reported by the United Nations. This projection emphasizes the urgent global need for advanced water management solutions like cloud-based analytics, which help optimize usage, detect leakages, and improve overall water resource sustainability in increasingly strained environments.

Key Market Challenges

Integration with Legacy Infrastructure and Existing Water Management Systems

One of the most significant challenges facing the global cloud-based water analytics market is the complexity involved in integrating modern analytics platforms with existing, often outdated, water management infrastructure. Water utilities and industrial operators in many regions, particularly in emerging economies, have traditionally relied on legacy systems characterized by manual operations, analog instrumentation, and siloed data environments. These legacy infrastructures were never designed with digital transformation in mind, making it difficult to seamlessly implement cloud-based analytics solutions. The process of retrofitting old systems with advanced sensors, real-time data acquisition tools, and cloud gateways requires both significant capital investment and specialized technical expertise. Furthermore, legacy infrastructure may lack the necessary digital interfaces or compatibility standards, resulting in extended project timelines, unexpected costs, and operational disruptions during the transition phase.

The challenge of integration is compounded by the diversity of water management systems across regions and industries. Different utilities may operate varying types of hardware, communication protocols, and software systems, creating fragmented environments that resist standardized cloud deployment. This heterogeneity necessitates customized integration strategies for each deployment, further driving up implementation complexity and cost. Moreover, water management is often critical infrastructure, and utilities are understandably cautious about adopting technologies that may compromise operational reliability or data integrity. Ensuring continuous service delivery while upgrading systems remains a delicate balance for operators. Cloud-based solutions must offer robust interoperability, secure data migration capabilities, and minimal downtime assurances to gain acceptance within such environments. Until these integration hurdles are systematically addressed, especially for small to medium-sized utilities with limited budgets, the growth potential of cloud-based water analytics will remain partially constrained.

Key Market Trends

Adoption of Artificial Intelligence and Machine Learning in Water Analytics

The increasing integration of artificial intelligence and machine learning into cloud-based water analytics platforms is transforming the way water resources are monitored, managed, and optimized. Artificial intelligence-driven solutions enable predictive analysis, anomaly detection, and automated decision-making, which enhance operational efficiency and reduce water loss. These advanced technologies process large volumes of real-time data collected from various sources, including sensors, smart meters, and satellite imagery, to provide actionable insights. Predictive maintenance models based on artificial intelligence help utilities anticipate equipment failures, pipeline leaks, or contamination events, minimizing service disruptions and maintenance costs.

Machine learning algorithms continuously improve the accuracy of water demand forecasting, leakage detection, and consumption pattern analysis by learning from historical and real-time data. This ability allows water utilities, municipalities, and industrial operators to make data-driven decisions and proactively manage water distribution networks. The integration of artificial intelligence into cloud platforms also supports dynamic optimization of water usage in agriculture, industrial processes, and smart city applications. As these technologies mature and become more accessible through cloud services, the adoption of artificial intelligence and machine learning in water analytics is expected to increase steadily, providing enhanced predictive capabilities and operational intelligence for users across diverse sectors.

Key Market Players

• ABB Ltd.
• General Electric Company
• IBM Corporation
• Microsoft Corporation
• Schneider Electric SE
• Siemens AG
• Oracle Corporation
• Suez SA

Report Scope:

In this report, the Global Cloud-based Water Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Cloud-based Water Analytics Market, By Component:

• Solutions
• Services

Cloud-based Water Analytics Market, By Deployment Mode:

• Public Cloud
• Private Cloud
• Hybrid Cloud

Cloud-based Water Analytics Market, By Application:

• Water Quality Monitoring
• Leakage Detection & Management
• Asset Management
• Demand Forecasting & Consumption Analytics
• Flood Monitoring & Disaster Management
• Regulatory Compliance & Reporting
• Wastewater Treatment Analytics

Cloud-based Water Analytics 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 Cloud-based Water Analytics Market.

Available Customizations:

Global Cloud-based Water Analytics Market report with the given market data, TechSci 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. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

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 Cloud-based Water Analytics Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Solutions, Services)
  • 5.2.2. By Deployment Mode (Public Cloud, Private Cloud, Hybrid Cloud)
  • 5.2.3. By Application (Water Quality Monitoring, Leakage Detection & Management, Asset Management, Demand Forecasting & Consumption Analytics, Flood Monitoring & Disaster Management, Regulatory Compliance & Reporting, Wastewater Treatment Analytics)
  • 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 Cloud-based Water Analytics 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 Mode
  • 6.2.3. By Application
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Cloud-based Water Analytics 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 Mode
      • 6.3.1.2.3. By Application
  • 6.3.2. Canada Cloud-based Water Analytics 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 Mode
      • 6.3.2.2.3. By Application
  • 6.3.3. Mexico Cloud-based Water Analytics 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 Mode
      • 6.3.3.2.3. By Application

7. Europe Cloud-based Water Analytics 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 Mode
  • 7.2.3. By Application
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Cloud-based Water Analytics 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 Mode
      • 7.3.1.2.3. By Application
  • 7.3.2. France Cloud-based Water Analytics 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 Mode
      • 7.3.2.2.3. By Application
  • 7.3.3. United Kingdom Cloud-based Water Analytics 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 Mode
      • 7.3.3.2.3. By Application
  • 7.3.4. Italy Cloud-based Water Analytics 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 Mode
      • 7.3.4.2.3. By Application
  • 7.3.5. Spain Cloud-based Water Analytics 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 Mode
      • 7.3.5.2.3. By Application

8. Asia Pacific Cloud-based Water Analytics 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 Mode
  • 8.2.3. By Application
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Cloud-based Water Analytics 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 Mode
      • 8.3.1.2.3. By Application
  • 8.3.2. India Cloud-based Water Analytics 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 Mode
      • 8.3.2.2.3. By Application
  • 8.3.3. Japan Cloud-based Water Analytics 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 Mode
      • 8.3.3.2.3. By Application
  • 8.3.4. South Korea Cloud-based Water Analytics 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 Mode
      • 8.3.4.2.3. By Application
  • 8.3.5. Australia Cloud-based Water Analytics 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 Mode
      • 8.3.5.2.3. By Application

9. Middle East & Africa Cloud-based Water Analytics 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 Mode
  • 9.2.3. By Application
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Cloud-based Water Analytics 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 Mode
      • 9.3.1.2.3. By Application
  • 9.3.2. UAE Cloud-based Water Analytics 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 Mode
      • 9.3.2.2.3. By Application
  • 9.3.3. South Africa Cloud-based Water Analytics 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 Mode
      • 9.3.3.2.3. By Application

10. South America Cloud-based Water Analytics 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 Mode
  • 10.2.3. By Application
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Cloud-based Water Analytics 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 Mode
      • 10.3.1.2.3. By Application
  • 10.3.2. Colombia Cloud-based Water Analytics 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 Mode
      • 10.3.2.2.3. By Application
  • 10.3.3. Argentina Cloud-based Water Analytics 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 Mode
      • 10.3.3.2.3. By Application

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. ABB Ltd.
  • 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. General Electric Company
• 13.3. IBM Corporation
• 13.4. Microsoft Corporation
• 13.5. Schneider Electric SE
• 13.6. Siemens AG
• 13.7. Oracle Corporation
• 13.8. Suez SA

14. Strategic Recommendations

15. About Us & Disclaimer