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增强分析市场规模、全球组件、部署模式、组织规模、地区、范围和预测

Global Augmented Analytics Market Size Component (Software, Services), By Deployment Mode (On-Premises, Cloud-Based), By Organization Size (Small And Medium-Sized Enterprises (SMEs), Large Enterprise), By Geographic Scope And Forecast

出版日期: 2025年05月02日 | 出版商:

Verified Market Research | 英文 202 Pages | 商品交期: 2-3个工作天内

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简介目录

增强分析市场及预测

增强分析市场规模在 2024 年价值 110.4 亿美元，预计到 2032 年将达到 601.2 亿美元，2026 年至 2032 年的复合年增长率为 23.6%。

增强智能分析是指利用人工智慧 (AI) 和机器学习 (ML) 来增强资料分析流程。该技术可自动执行资料准备、分析和视觉化等复杂资料任务，使用户无需深厚的专业知识即可获得进阶洞察。增强分析利用演算法识别模式并产生预测模型，简化了从海量资料集中获取可行洞察的过程。
事实上，增强分析正在透过实现更直观的数据互动和更快的决策来改变各行各业。
例如，在金融业，它有助于预测市场趋势并更准确地检测诈欺行为；在医疗保健行业，它透过分析大量医疗数据来帮助诊断和规划患者的治疗方案；在零售业，它被广泛用于个人化客户体验和优化供应链营运。

全球增强分析市场动态

关键市场驱动因素

人工智慧和机器学习的不断进步：人工智慧和机器学习技术的持续改进将透过增强自动数据处理、模式识别和预测分析的能力来推动增强分析市场的发展。这些进步使得从复杂资料集中获取可操作的洞察变得更加容易。根据美国国家科学基金会 (NSF) 于 2024 年 1 月发布的报告，美国联邦政府对人工智慧研究的资助将在 2020 年至 2023 年间成长 30%，达到每年 25 亿美元。这些投资已显着提升了人工智慧的能力。
资料量不断增长：各行各业产生的资料量呈指数级增长，需要更先进的分析工具。增强分析透过提供可扩展的解决方案来有效管理和解读大量数据，从而推动更明智的决策，从而满足了这一需求。例如，亚马逊网路服务 (AWS) 于 2024 年 2 月宣布升级其「资料湖形成」服务，旨在更有效率地处理Petabyte级资料湖，满足日益增长的大规模资料管理解决方案需求。
对即时洞察的需求日益增长：企业越来越需要即时数据分析来保持竞争力。增强分析透过自动化数据处理和分析提供及时洞察，从而能够更快地响应市场变化和业务挑战。例如，微软于2024年4月宣布了其Power BI平台的增强功能，包括改进的即时资料处理功能以及与Azure Synapse Analytics的集成，以更快地产生洞察。
自助式分析的采用日益增长：对自助式分析工具的需求日益增长，这些工具能够帮助非技术用户独立进行数据分析。增强分析透过提供直觉的介面和自动化洞察，使数据存取和分析更加民主化，从而顺应了这一趋势。商业应用研究中心 (BARC) 在其《2024 年商业智慧趋势监测报告》中报告称，2022 年至 2023 年间，自助式商业智慧工具的使用量将增长 22%，76% 的受访组织计划在未来两年内增加对这些技术的投资。

主要挑战

资料隐私和安全疑虑日益加剧：增强分析的使用引发了重大的资料隐私和安全问题，尤其是在敏感资讯方面。确保强有力的保护措施和法规合规性可能非常复杂，并可能成为其应用的阻碍。
技能差距不断扩大：儘管人们努力简化分析，但仍需要熟练的专业人员来管理和解读增强分析工具带来的见解。合格资料科学家和分析师的短缺可能会限制其有效应用。
过度依赖自动化系统：过度依赖自动化分析会减少人工监督和批判性思维，如果不谨慎管理，可能会导致对数据的误解和未能考虑上下文的细微差别。
日益严重的资料品质问题：增强分析高度依赖输入资料的品质。品质差或不一致的数据可能导致不准确或误导性的洞察，从而削弱分析工具的有效性。
变革阻力：企业可能会遭遇习惯于传统分析方法的员工的阻力。采用增强分析需要文化转型，并愿意接受新技术和新工作流程。

主要趋势

人工智慧和机器学习的日益普及：将先进的人工智慧和机器学习演算法整合到增强分析平台的趋势日益增长。这一趋势增强了预测能力，并自动化了复杂的数据分析，从而获得更准确、更可操作的洞察。例如，IBM 于 2024 年 3 月宣布推出其「Watson AutoAI」平台。该平台实现了从资料准备到模型选择和部署的整个机器学习流程的自动化，显着减少了将人工智慧引入分析工作流程所需的时间和专业知识。
自助式分析工具的扩展：市场上自助式分析工具的数量正在增长，这些工具允许非技术用户自行进行数据分析。此趋势源自于人们渴望进一步普及洞察获取途径，并赋能用户自主做出数据主导决策。美国国家教育统计中心 (NCES) 于 2023 年 12 月报告称，65% 的美国高等教育机构提供资料素养和自助式分析课程或项目，高于 2021 年的 47%。
与云端运算整合：增强分析解决方案越来越多地透过云端平台部署，云端平台具有可扩展性、灵活性和成本效益。这一趋势使企业能够利用云端资源提供强大的分析能力，而无需在基础设施上进行大量的前期投资。例如，2024年4月，微软Azure宣布其「Azure Synapse Analytics」服务正式上线，该服务将巨量资料分析、人工智慧与云端原生功能结合，使企业能够在云端无缝运行分析工作负载。

Augmented analytics refers to the use of artificial intelligence (AI) and machine learning (ML) to enhance data analytics processes. This technology automates complex data tasks, such as data preparation, analysis, and visualization, making advanced insights more accessible to users without deep technical expertise. By leveraging algorithms to identify patterns and generate predictive models, augmented analytics simplifies the process of deriving actionable insights from large datasets.
In practice, augmented analytics is transforming various industries by enabling more intuitive data interaction and faster decision-making.
For instance, in finance, it helps in predicting market trends and detecting fraudulent activities with higher accuracy. In healthcare, it aids in patient diagnosis and treatment planning by analyzing vast amounts of medical data. The technology is also widely used in retail for personalizing customer experiences and optimizing supply chain operations.

Global Augmented Analytics Market Dynamics

The key market dynamics that are shaping the global Augmented Analytics Market include:

Key Market Drivers

Increasing Advancements in AI and Machine Learning: Continuous improvements in AI and machine learning technologies drive the augmented analytics market by enhancing the capabilities for automated data processing, pattern recognition, and predictive analytics. These advancements make it easier to generate actionable insights from complex datasets. According to a report by the National Science Foundation (NSF) released in January 2024, federal funding for AI research in the United States increased by 30% between 2020 and 2023, reaching USD 2.5 Billion annually. This investment has led to significant advancements in AI capabilities.
Increased Data Volumes: The exponential growth in data generated across industries necessitates more sophisticated tools for analysis. Augmented analytics addresses this need by providing scalable solutions that can efficiently manage and interpret large volumes of data, facilitating better decision-making. For instance, Amazon Web Services (AWS) introduced its "Data Lake Formation" service upgrade in February 2024, designed to handle petabyte-scale data lakes more efficiently, addressing the growing need for large-scale data management solutions.
Increasing Demand for Real-time Insights: Organizations increasingly require real-time data analysis to stay competitive. Augmented analytics delivers timely insights by automating data processing and analysis, enabling faster responses to market changes and operational challenges. For instance, in April 2024, Microsoft announced enhancements to its Power BI platform, including improved real-time data processing capabilities and integration with Azure Synapse Analytics for faster insights generation.
Growing Adoption of Self-service Analytics: There is a rising demand for self-service analytics tools that empower non-technical users to perform data analysis independently. Augmented analytics supports this trend by providing intuitive interfaces and automated insights, democratizing data access and analysis. The Business Application Research Center (BARC) reported in their "BI Trend Monitor 2024" that self-service BI tools usage increased by 22% between 2022 and 2023, with 76% of surveyed organizations planning to invest more in these technologies over the next two years.

Key Challenges:

Rising data Privacy and Security Concerns: The use of augmented analytics raises significant data privacy and security issues, particularly with sensitive information. Ensuring robust protection and regulatory compliance can be complex and may deter adoption.
Growing Skills Gap: Despite efforts to simplify analytics, there remains a need for skilled professionals to manage and interpret insights from augmented analytics tools. The shortage of qualified data scientists and analysts can limit effective implementation.
Over-reliance on Automated Systems: Excessive dependence on automated analytics can reduce human oversight and critical thinking. This may lead to misinterpretation of data or failure to account for contextual nuances if not carefully managed.
Growing data Quality Issues: Augmented analytics heavily relies on the quality of input data. Poor data quality or inconsistencies can lead to inaccurate or misleading insights, undermining the effectiveness of the analytics tools.
Resistance to Change: Organizations may encounter resistance from employees accustomed to traditional analytics methods. Adopting augmented analytics requires a cultural shift and willingness to embrace new technologies and workflows.

Key Trends

Increased Adoption of AI and Machine Learning: There is a growing trend towards integrating advanced AI and machine learning algorithms in augmented analytics platforms. This trend enhances predictive capabilities and automates complex data analysis, leading to more accurate and actionable insights. For instance, in March 2024, IBM announced the launch of its "Watson AutoAI" platform, which automates the entire machine learning pipeline from data preparation to model selection and deployment, significantly reducing the time and expertise required for implementing AI in analytics workflows.
Growing expansion of Self-service Analytics Tools: The market is seeing a rise in self-service analytics tools that empower non-technical users to conduct their own data analyses. This trend is driven by the desire for more democratized access to insights and the ability for users to make data-driven decisions independently. The National Center for Education Statistics (NCES) reported in December 2023 that 65% of U.S. higher education institutions were offering courses or programs in data literacy and self-service analytics, up from 47% in 2021.
Integration with Cloud Computing: Augmented analytics solutions are increasingly being deployed via cloud platforms, offering scalability, flexibility, and cost-efficiency. This trend allows organizations to leverage cloud resources for powerful analytics without heavy upfront investments in infrastructure. For instance, in April 2024, Microsoft Azure announced the general availability of its "Azure Synapse Analytics" service, which combines big data analytics and AI with cloud-native capabilities, enabling organizations to run analytics workloads seamlessly in the cloud.

Global Augmented Analytics Market Regional Analysis

Here is a more detailed regional analysis of the global Augmented Analytics Market:

Asia Pacific

The Asia-Pacific region is emerging as a leading force in the augmented analytics market, leveraging its rapid technological advancements and large-scale digital transformation initiatives. This growth trajectory is driven by increasing investments in artificial intelligence and machine learning technologies across various sectors.
Several factors contribute to this dominance, including the surge in data generation and the need for sophisticated data analysis tools. For instance, the Indian government's Ministry of Electronics and Information Technology has reported a significant rise in data usage and digital engagement, with an expected 25% increase in demand for advanced analytics solutions by 2025. Additionally, the rise of smart cities and the adoption of IoT technologies across countries like China and Japan further fuel the demand for augmented analytics.
Recent developments from top market players underscore the region's importance. For example, in August 2024, SAP announced a major expansion of its analytics cloud services in Asia-Pacific, aiming to cater to the growing demand for advanced data analytics solutions. Similarly, Oracle has launched a new suite of AI-powered analytics tools tailored specifically for the APAC market, reflecting the region's increasing influence and the high level of innovation taking place. These moves are indicative of the Asia-Pacific region's central role in shaping the future of augmented analytics.

North America

North America stands out as a mature market in augmented analytics, driven by its early adoption of advanced technologies and a robust ecosystem of technology firms. The region's dominance in this field is underpinned by its substantial investments in data analytics and artificial intelligence. According to the U.S. Census Bureau, the U.S. augmented analytics market is projected to reach $20 billion by the end of 2024, reflecting its established position and ongoing growth in this sector.
Key drivers of North America's mature status include the extensive integration of augmented analytics tools across various industries such as finance, healthcare, and retail. The U.S. Bureau of Economic Analysis reported a 15% increase in enterprise spending on data analytics technologies in 2023, illustrating the strong demand for advanced analytics solutions. Additionally, the proliferation of big data and the increasing need for actionable insights to drive business decisions further fuel the market's expansion.

Global Augmented Analytics Market: Segmentation Analysis

The Global Augmented Analytics Market is segmented on the basis of Component, Deployment Mode, Organization Size, and Geography.

Augmented Analytics Market, By Component

Software
Services

Based on Component, the Global Augmented Analytics Market is a divided into Software and Services. In the augmented analytics market, the software segment is currently dominating, driven by the increasing adoption of advanced analytics tools and platforms that leverage AI and machine learning for data analysis and visualization. However, the services segment is experiencing rapid growth, reflecting a rising demand for consulting, implementation, and support services to help organizations effectively deploy and integrate augmented analytics solutions. This growing trend highlights the need for expert guidance in maximizing the value of these advanced tools.

Augmented Analytics Market, By Deployment Mode

On-Premises
Cloud-Based

Based on Deployment Mode, the Global Augmented Analytics Market is divided into On-Premises and Cloud-Based. In the augmented analytics market, the cloud-based deployment mode is currently dominating due to its scalability, flexibility, and cost-effectiveness, which align with the increasing preference for cloud solutions across various industries. However, the on-premises deployment mode is experiencing rapid growth, driven by organizations with stringent data security and regulatory requirements that necessitate more control over their analytics infrastructure. This growing segment reflects the ongoing need for robust and secure data management solutions in specific sectors.

Augmented Analytics Market, By Organization Size

Small And Medium-Sized Enterprises (SMEs)
Large Enterprise

Based on Organization Size, the market is divided into Small And Medium-Sized Enterprises (SMEs) and Large Enterprise. In the augmented analytics market, large enterprises are currently dominating, thanks to their substantial budgets and greater capacity to invest in advanced analytics technologies. However, the small and medium-sized enterprises (SMEs) segment is experiencing rapid growth, driven by the increasing availability of cost-effective, scalable solutions that cater to the needs of smaller organizations. This trend indicates a growing democratization of advanced analytics tools, making them more accessible to SMEs seeking to enhance their data-driven decision-making capabilities.

Augmented Analytics Market, By Geography

North America
Europe
Asia Pacific
Rest of the World

Based on Geography, the Global Augmented Analytics Market is classified into North America, Europe, Asia Pacific, and the Rest of the World. In the augmented analytics market, North America is currently dominating, owing to its advanced technological infrastructure, high adoption rates of cutting-edge analytics solutions, and a strong presence of key market players. Meanwhile, the Asia Pacific region is rapidly growing, driven by increasing digital transformation initiatives, a burgeoning tech-savvy population, and expanding investments in analytics capabilities by businesses across various sectors. This dynamic growth in Asia Pacific underscores the region's rising prominence in the global augmented analytics landscape.

Key Players

The "Global Augmented Analytics Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are Domo, Inc., International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, QlikTech International AB, Salesforce, Inc., SAP SE, Sisense, Inc., ThoughtSpot, Inc., TIBCO Software, Inc. and Yellowfin International Pty Ltd (Idera, Inc.).

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with its product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Key Developments

In October 2022, Salesforce launched Einstein Analytics Pro, integrating augmented analytics features into its CRM platform. This release focuses on leveraging machine learning to deliver predictive insights and personalized recommendations to sales and marketing teams.
In February 2021, SAS Institute introduced SAS Viya with augmented analytics functionalities. This platform aims to simplify data exploration and enhance decision-making through advanced AI and machine learning models.
In November 2020, Tableau Software announced a new suite of augmented analytics tools within its Tableau CRM. The tools provide enhanced data visualization and automatic trend analysis, aiming to improve user experience and insight generation.

1. Introduction

Market Definition
Market Segmentation
Research Methodology

2. Executive Summary

Key Findings
Market Overview
Market Highlights

3. Market Overview

Market Size and Growth Potential
Market Trends
Market Drivers
Market Restraints
Market Opportunities
Porter's Five Forces Analysis

4. Augmented Analytics Market, By Component

Software
Services

5. Augmented Analytics Market, By Deployment Mode

Cloud-Based
On-Premises

6. Augmented Analytics Market, By Organization Size

Small And Medium-Sized Enterprises (SMEs)
Large Enterprises

7. Regional Analysis

North America
United States
Canada
Mexico
Europe
United Kingdom
Germany
France
Italy
Asia-Pacific
China
Japan
India
Australia
Latin America
Brazil
Argentina
Chile
Middle East and Africa
South Africa
Saudi Arabia
UAE

8. Market Dynamics

Market Drivers
Market Restraints
Market Opportunities
Impact of COVID-19 on the Market

9. Competitive Landscape

Key Players
Market Share Analysis

10. Company Profiles

Domo, Inc.
International Business Machines Corporation
Microsoft Corporation
Oracle Corporation
QlikTech International AB
Salesforce, Inc.
SAP SE
Sisense, Inc.
ThoughtSpot, Inc.
TIBCO Software, Inc.
Yellowfin International Pty Ltd (Idera, Inc.).

11. Market Outlook and Opportunities

Emerging Technologies
Future Market Trends
Investment Opportunities

12. Appendix

List of Abbreviations
Sources and References

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增强分析市场规模、全球组件、部署模式、组织规模、地区、范围和预测