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全球数据集成市场 - 2023-2030
市场调查报告书
商品编码
1297827

全球数据集成市场 - 2023-2030

Global Data Integration Market - 2023-2030
出版日期: | 出版商: DataM Intelligence | 英文 210 Pages | 商品交期: 约2个工作天内

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简介目录

市场概况

全球数据集成市场在2022年达到116亿美元，预计到2030年将达到263亿美元，在2023-2030年的预测期内，年复合增长率为10.8%。随着发展中国家政府服务的不断数字化，全球数据集成市场将见证持续增长。由于政府正在努力改善公民获得公共服务的机会并减少腐败，来自不同来源的各种数据点的整合变得非常重要。这将导致对定制数据集成工具和服务的需求增加。

全球数据整合市场正经历着激烈的竞争。主要参与者正在进行战略收购，以巩固其在市场上的地位。例如，2023年5月，总部设在美国的软件公司Qlik宣布收购另一家专门从事数据集成技术的美国公司Talend Inc.。这次收购预计将大大改善Qlik的数据整合平台产品的质量。

市场动态

业务流程自动化的兴起

企业越来越多地采用业务流程自动化来简化操作，提高效率，并减少人工操作。企业实施各种自动化系统，如企业资源规划（ERP）、客户关系管理（CRM）、供应链管理（SCM）和人力资源管理（HRM）系统，以优化其运作。

通过连接和整合各种自动化系统、应用程序和工作流程中的数据，数据整合在业务流程自动化中发挥了关键作用。整合后的数据能够实现不同流程之间的无缝信息流，使企业能够实现端到端的业务流程自动化，并实现更大的运营效率。

数据整合确保自动化系统之间流动的数据是一致和准确的。它涉及数据验证、清理、转换和映射，以统一数据格式、结构和语义。通过整合保持数据的一致性和准确性，企业可以依靠可靠的数据进行决策、报告、合规性和其他关键业务流程。

对实时洞察力的需求不断增加

实时洞察力使企业能够做出及时和明智的决策。在现代快节奏的商业环境中，企业需要从各种来源获得最新的信息，以快速应对市场变化、客户需求和新出现的机会。数据整合在实时收集、汇总和分析数据方面发挥了关键作用，确保组织对其运营有一个全面和准确的看法，以便作出有效的决策。

实时的洞察力使企业能够不断监测和优化其业务绩效。通过实时整合多个来源的数据，企业可以获得对其运营、客户互动、供应链和其他关键领域的整体看法。实时可见性使他们能够识别瓶颈，发现趋势，并采取主动行动，以提高效率，降低成本，优化资源配置，并提高整体业务绩效。

缺少互操作性

数据整合涉及连接和整合来自不同系统、应用程序和平台的数据。然而，不同的系统往往使用不同的数据格式、协议和标准，使得数据的无缝交换和整合变得困难。系统之间缺乏互操作性在数据整合过程中造成了障碍，阻碍了数据在不同环境中的顺利流动。

许多企业在混合IT环境中运作，将企业内部系统与云平台和第三方应用程序相结合。这些不同的环境之间缺乏互操作性，造成了整合的挑战。数据整合解决方案必须能够在这些不同的环境中无缝连接和整合数据，以确保数据的一致性和可访问性。缺乏互操作性阻碍了混合环境下的数据整合。

许多组织变得依赖特定供应商的专有技术、格式或平台。这可能会限制数据集成解决方案与其他系统或平台的互操作性。由于兼容性问题，组织在整合来自不同供应商的数据或在供应商之间过渡时可能面临挑战。对供应商锁定的恐惧成为采用数据整合解决方案的阻力。

COVID-19影响分析

COVID-19的大流行迫使企业加快他们的数字化转型计划，以适应远程工作、在线操作和不断变化的客户行为。它导致了对数据整合解决方案的需求增加，以连接和整合来自不同系统的数据，并在分布式环境中实现无缝操作。

大流行病造成的不确定性突出了实时洞察力对决策的重要性。大流行病引起的深刻变化在大流行病后时期才会加速。后大流行时期可能会见证全球主要行业越来越多地采用数据整合。

人工智能影响分析

人工智能技术，如机器学习和自然语言处理，正在被整合到数据整合解决方案中。由人工智能驱动的数据整合能够实现智能数据映射、数据清洗和数据转换，提高整合过程的效率和准确性。

人工智能使数据整合中的重复性任务自动化，减少人工努力，加快整合过程。人工智能算法可以分析数据结构并建议最佳的整合工作流程，简化了整合管道的开发和维护。人工智能还通过识别集成数据中的模式、异常和关联性来增强人类的能力，使组织能够获得有价值的见解。

俄罗斯-乌克兰战争的影响

冲突扰乱了乌克兰的数据整合市场。许多乌克兰私营企业在国外建立了自己的公司，这导致了对数据集成工具和服务的需求暂时上升，因为企业要确保连续性。此外，乌克兰政府也看到了需求的增加，因为它试图在战争期间维持一些关键的政府服务。

西方国家在冲突后对俄罗斯实施的制裁导致了俄罗斯数据集成市场的重大混乱。由于西方公司因制裁而停止运营，许多俄罗斯行业被剥夺了数据集成工具和服务。这导致了国内软件供应商的需求增加。

目录

第一章：方法和范围

  • 研究方法
  • 报告的研究目标和范围

第二章：定义和概述

第三章：执行摘要

  • 按部署方式抽查
  • 按组件分类
  • 按应用分类
  • 按终端用户分类
  • 按地区分类

第4章：动态变化

  • 影响因素
    • 驱动因素
      • 对数据驱动决策的需求不断增长
      • 越来越多地采用数字化转型措施
      • 业务流程自动化的增加
      • 对实时洞察力的需求不断增加
    • 限制因素
      • 对数据安全和隐私的关注度不断提高
      • 缺少互操作性
    • 机会
    • 影响分析

第五章：行业分析

  • 波特的五力分析
  • 供应链分析
  • 价格分析
  • 监管分析

第六章：COVID-19分析

  • 对COVID-19的分析
    • COVID之前的情况
    • COVID期间的情况
    • COVID之后的情况
  • COVID-19期间的定价动态
  • 需求-供应谱系
  • 大流行期间与市场有关的政府倡议
  • 制造商的战略倡议
  • 结语

第七章：按部署方式

  • 内部部署
  • 随需应变

第8章：按组件分类

  • 服务
  • 工具

第九章：按应用分类

  • 人力资源 (HR)
  • 市场和销售
  • 运营

第十章：按终端用户分类

  • 银行业金融机构
  • 政府和国防
  • IT和电信
  • 医疗保健和生命科学
  • 其他行业

第十一章：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 意大利
    • 西班牙
    • 欧洲其他地区
  • 南美洲
    • 巴西
    • 阿根廷
    • 南美其他地区
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 澳大利亚
    • 亚太其他地区
  • 中东和非洲

第十二章 ：竞争格局

  • 竞争格局
  • 市场定位/份额分析
  • 合併和收购分析

第十三章 ：公司简介

  • Cisco Systems, Inc.
    • 公司概述
    • 部署方法组合和说明
    • 财务概况
    • 最近的发展情况
  • IBM
  • Oracle Corporation
  • SAP SE
  • Microsoft
  • Precisely
  • QlikTech International AB
  • Informatica Inc.
  • SAS Institute Inc.
  • Actian Corporation

第十四章：附录

简介目录
Product Code: ICT666

Market Overview

The Global Data Integration Market reached US$ 11.6 billion in 2022 and is expected to reach US$ 26.3 billion by 2030, growing with a CAGR of 10.8% during the forecast period 2023-2030. The global data integration market will witness continued growth with the ongoing digitization of government services in developing countries. As governments are striving to improve access to public services for citizens and reduce corruption, the integration of various data points from different sources attains importance. It will lead to an increase in demand for customized data integration tools and services.

The global data integration market is witnessing intense competition. Major players are undertaking strategic acquisitions to consolidate their position in the market. For instance, in May 2023, Qlik, a U.S.-based software company, announced the acquisition of Talend Inc., another U.S.-based company specializing in data integration technologies. The acquisition is expected to significantly improve the quality of Qlik's data integration platform offerings.

Market Dynamics

Rise in Business Process Automation

Organizations are increasingly adopting business process automation to streamline operations, improve efficiency, and reduce manual effort. Organizations implement various automated systems, such as enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM), and human resources management (HRM) systems, to optimize their operations.

Data integration plays a crucial role in business process automation by connecting and integrating data across various automated systems, applications, and workflows. Integrated data enables seamless information flow between different processes, allowing organizations to automate end-to-end business processes and achieve greater operational efficiency.

Data integration ensures that data flowing between automated systems is consistent and accurate. It involves data validation, cleansing, transformation, and mapping to align data formats, structures, and semantics. By maintaining data consistency and accuracy through integration, organizations can rely on reliable data for decision making, reporting, compliance, and other critical business processes.

Increasing Demand For Real-Time Insights

Real-time insights enable organizations to make timely and informed decisions. In the modern fast-paced business environment, organizations need access to up-to-date information from various sources to respond quickly to market changes, customer needs, and emerging opportunities. Data integration plays a crucial role in collecting, aggregating, and analyzing data in real time, ensuring that organizations have a comprehensive and accurate view of their operations for effective decision making.

Real-time insights empower organizations to monitor and optimize their business performance continuously. By integrating data from multiple sources in real time, organizations can gain a holistic view of their operations, customer interactions, supply chain, and other key areas. The real-time visibility allows them to identify bottlenecks, spot trends, and take proactive actions to improve efficiency, reduce costs, optimize resource allocation, and enhance overall business performance.

Lack of Interoperability

Data integration involves connecting and integrating data from various systems, applications, and platforms. However, different systems often use different data formats, protocols, and standards, making it difficult to seamlessly exchange and integrate data. The lack of interoperability between systems creates obstacles in the data integration process and hampers the smooth flow of data across different environments.

Many organizations operate in hybrid IT environments, combining on-premises systems with cloud platforms and third-party applications. The lack of interoperability between these disparate environments creates integration challenges. Data integration solutions must be able to seamlessly connect and integrate data across these diverse environments to ensure data consistency and accessibility. The absence of interoperability impedes the integration of data in hybrid environments.

Many organizations become dependent on a specific vendor's proprietary technologies, formats, or platforms. It can limit the interoperability of data integration solutions with other systems or platforms. Organizations may face challenges in integrating data from different vendors or transitioning between vendors due to compatibility issues. The fear of vendor lock-in acts as a deterrent to adopting data integration solutions.

COVID-19 Impact Analysis

The COVID-19 pandemic forced organizations to accelerate their digital transformation initiatives to adapt to remote work, online operations, and changing customer behaviors. It led to an increased demand for data integration solutions to connect and integrate data from various systems and enable seamless operations in a distributed environment.

The uncertainty caused by the pandemic highlighted the importance of real-time insights for decision-making. The profound changes caused by the pandemic only accelerated in the post-pandemic period. The post-pandemic period is likely to witness increasing adoption of data integration by major industries globally.

AI Impact Analysis

AI technologies, such as machine learning and natural language processing, are being integrated into data integration solutions. AI-powered data integration enables intelligent data mapping, data cleansing, and data transformation, improving the efficiency and accuracy of the integration process.

AI automates repetitive tasks in data integration, reducing manual effort and speeding up the integration process. AI algorithms can analyze data structures and suggest optimal integration workflows, simplifying the development and maintenance of integration pipelines. AI also augments human capabilities by identifying patterns, anomalies, and correlations in integrated data, enabling organizations to derive valuable insights.

Russia- Ukraine War Impact

The conflict disrupted the data integration market in Ukraine. Many private Ukrainian businesses established themselves abroad which led to a temporary rise in demand for data integration tools and services as businesses sought to ensure continuity. Furthermore, increased demand was also witnessed by the Ukrainian government as it sought to maintain some critical government services during the war.

Sanctions imposed on Russia by Western countries in the wake of the conflict have led to major disruptions in the Russian data integration market. Many Russian industries have been deprived of data integration tools and services as western companies ceased operations due to sanctions. It has led to increased demand from domestic software vendors.

Segment Analysis

The global data integration market is segmented based on deployment method, component, application, end-user and region.

Data Integration Tools are the Most Widely Used Component of the Global Market

Data integration tools provide the necessary software and infrastructure to facilitate the integration of data from various sources. The tools offer features like data extraction, transformation, cleansing, mapping, and loading (ETL), data synchronization, data virtualization, and data replication. The tools provide a user-friendly interface and a range of functionalities to support the integration process.

Data integration tools cater to a wide range of use cases, making them applicable across industries and business functions. The tools support integration requirements for data warehousing, business intelligence, cloud migration, application integration, master data management, data governance, and more. The versatility of data integration tools makes them widely adopted by organizations across various sectors.

Geographical Analysis

Asia-Pacific is Expected to Grow at a Faster Pace During the Forecast Period

The Asia-Pacific data integration market is expected to grow at a faster CAGR of 12.5% during the forecast period. Asia-Pacific is witnessing robust economic growth, with countries like China, India, Vietnam and Malaysia having some of the highest growth rates. The rapid economic growth is expected to create new growth opportunities for the data integration market.

Asia-Pacific is embracing digital transformation initiatives across various industries. Organizations are adopting advanced technologies such as cloud computing, big data analytics, AI, and IoT to drive efficiency, innovation, and customer-centricity. Data integration is playing a critical role in connecting and integrating data from different sources and systems, enabling organizations to leverage the utility of these technologies.

The adoption of cloud computing is witnessing a significant rise in Asia-Pacific. Organizations are leveraging cloud-based data integration solutions to overcome infrastructure limitations, improve scalability, and reduce IT costs. The region's expanding cloud infrastructure and investment in data centers is also contributing to the growth of the Asia-Pacific data integration market.

Competitive Landscape

The major global players include: Cisco Systems, Inc., IBM, Oracle Corporation, SAP SE, Microsoft, Precisely, QlikTech International AB, Informatica Inc., SAS Institute Inc. and Actian Corporation.

Why Purchase the Report?

  • To visualize the global data integration market segmentation based on deployment method, component, application, end-user and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of data integration market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as Excel consisting of key products of all the major players.

The global data integration market report would provide approximately 64 tables, 67 figures and 210 Pages.

Target Audience 2023

  • Data-Driven Businesses
  • Data Management System Companies
  • Industry Investors/Investment Bankers
  • Research Professionals

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Deployment Method
  • 3.2. Snippet by Component
  • 3.3. Snippet by Application
  • 3.4. Snippet by End-User
  • 3.5. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Growing Need for Data-Driven Decision Making
      • 4.1.1.2. Increasing Adoption of Digital Transformation Initiatives
      • 4.1.1.3. Rise in Business Process Automation
      • 4.1.1.4. Increasing Demand for Real-Time Insights
    • 4.1.2. Restraints
      • 4.1.2.1. Growing Concerns about Data Security and Privacy
      • 4.1.2.2. Lack of Interoperability
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis

6. COVID-19 Analysis

  • 6.1. Analysis of COVID-19
    • 6.1.1. Scenario Before COVID
    • 6.1.2. Scenario During COVID
    • 6.1.3. Scenario Post COVID
  • 6.2. Pricing Dynamics Amid COVID-19
  • 6.3. Demand-Supply Spectrum
  • 6.4. Government Initiatives Related to the Market During Pandemic
  • 6.5. Manufacturers Strategic Initiatives
  • 6.6. Conclusion

7. By Deployment Method

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 7.1.2. Market Attractiveness Index, By Deployment Method
  • 7.2. On-premises*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. On-demand

8. By Component

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 8.1.2. Market Attractiveness Index, By Component
  • 8.2. Services*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Tools

9. By Application

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 9.1.2. Market Attractiveness Index, By Application
  • 9.2. Human Resources (HR)*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Marketing & Sales
  • 9.4. Operations

10. By End-User

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 10.1.2. Market Attractiveness Index, By End-User
  • 10.2. BFSI*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Government & Defence
  • 10.4. IT and Telecommunications
  • 10.5. Healthcare & Life Sciences
  • 10.6. Others

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.7.1. The U.S.
      • 11.2.7.2. Canada
      • 11.2.7.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.7.1. Germany
      • 11.3.7.2. The UK
      • 11.3.7.3. France
      • 11.3.7.4. Italy
      • 11.3.7.5. Spain
      • 11.3.7.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.7.1. Brazil
      • 11.4.7.2. Argentina
      • 11.4.7.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.7.1. China
      • 11.5.7.2. India
      • 11.5.7.3. Japan
      • 11.5.7.4. Australia
      • 11.5.7.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Method
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

  • 12.1. Competitive Scenario
  • 12.2. Market Positioning/Share Analysis
  • 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

  • 13.1. Cisco Systems, Inc.*
    • 13.1.1. Company Overview
    • 13.1.2. Deployment Method Portfolio and Description
    • 13.1.3. Financial Overview
    • 13.1.4. Recent Developments
  • 13.2. IBM
  • 13.3. Oracle Corporation
  • 13.4. SAP SE
  • 13.5. Microsoft
  • 13.6. Precisely
  • 13.7. QlikTech International AB
  • 13.8. Informatica Inc.
  • 13.9. SAS Institute Inc.
  • 13.10. Actian Corporation

LIST NOT EXHAUSTIVE

14. Appendix

  • 14.1. About Us and Services
  • 14.2. Contact Us