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TechTarget:2024年AI在分析与商业智能领域的潜力与应用研究报告(英文版)(28页).pdf

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1、Unleashing the Power of AI in Analytics and Business Intelligence1 2024 TechTarget,Inc.All Rights Reserved.Back to contents 2024 TechTarget,Inc.All Rights Reserved.Unleashing the Power of AI in Analytics and Business IntelligenceJanuary 2024Mike Leone|Principal AnalystENTERPRISE STRATEGY GROUPUnleas

2、hing the Power of AI in Analytics and Business Intelligence2 2024 TechTarget,Inc.All Rights Reserved.Research ObjectivesAs organizations continue to recognize the importance of data-driven decision-making,the pace of business is preventing analytics success.The ever-increasing volume of distributed

3、data available to the business overwhelms data-centric stakeholders.As organizations struggle to gain a comprehensive picture of their data,yet another layer of complexity presents itself:rate of change.With the rate of change in the business often being faster than the rate at which data can be col

4、lected and analyzed,organizations need help ensuring the timely delivery of accurate insights based on the current state of the business.To address these challenges,organizations are turning to AI tools that eliminate manual processes to improve efficiency,promote productivity,and democratize analyt

5、ics.Whether through augmented analytics or generative AI(GenAI),stakeholders can be empowered to quickly and easily access,analyze,explore,and visualize data in a collaborative way.To gain further insight into these trends,TechTargets Enterprise Strategy Group surveyed 375 data and IT professionals

6、at organizations in North America (US and Canada)involved with or responsible for evaluating,purchasing,managing,and building analytics and business intelligence solutions.This study sought to:Identify the benefits organizations seek and realize from infusing AI into analytics and business intellige

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本文主要讨论了AI在分析和商业智能中的作用和挑战。主要观点包括: 1. 97%的组织在过去一年中增加了对分析和商业智能的投资,89%的组织计划在未来增加预算。 2. 数据质量和一致性是组织面临的主要挑战,同时数据安全和隐私也是重要问题。 3. 增强分析和生成式AI是当前和未来BI能力的主要方向。 4. 语义层是支持分析和BI的关键组件,与AI和ML技术紧密相关。 5. 高级领导和IT部门是分析和BI技术采购的主要影响者和预算持有者。 6. 组织正在部署策略来更好地启用用户使用分析和BI,包括自动化、自助服务和AI。 7. 定制解决方案可以提高用户体验和平台效果,但也会影响供应商忠诚度。 8. 组织正在采取措施来提高AI平台的用户采用率,包括采用新供应商、生成式AI和增加现有供应商的支出。
数据分析中AI的应用有哪些挑战? 如何提高员工对BI和AI平台的参与度? 企业如何利用AI实现数据分析的自动化?
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