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提升数据智能化：行业领袖关于数据和 AI 的关键洞察_AI阅读总结 — 包阅AI

by baoyueai

包阅导读总结

1.

关键词：数据、人工智能、行业领袖、创新、业务价值

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总结：本文探讨了数据和人工智能交叉领域的重要性，引述行业专家观点，涵盖技术融入数据管理、数据安全与访问控制、数据普及使用、元数据作用及平衡创新与风险等，强调打好数据基础以挖掘 AI 潜力和降低风险。

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主要内容：

– 行业趋势

– 多数 IT 领导将 AI 解决方案列为 2024 投资重点。

– 专家观点

– 来自 Informatica 的 Rik Tamm-Daniels 强调将 AI 融入数据管理，加速流程并简化用户交互。

– Immuta 的 Chris Brown 关注数据安全，包括识别敏感数据位置、制定访问规则和实施自动化政策。

– Dataiku 的 Conor Jensen 重视数据的普及访问和使用平衡。

– 专家们一致认可元数据在 AI 应用中的关键作用。

– Databricks 的 Robin Sutara 谈及生成式 AI 对人员、流程和变更管理的影响。

– 结论

– 组织需关注数据基础等方面，以充分利用 AI 潜力并降低风险。

思维导图：

文章地址：https://www.databricks.com/blog/elevating-data-intelligence-key-insights-industry-leaders-data-and-ai

文章来源：databricks.com

作者：Databricks

发布时间：2024/8/9 7:27

语言：英文

总字数：629字

预计阅读时间：3分钟

评分：88分

标签：数据和 AI 集成,数据管理,AI 安全,数据可访问性,行业洞察

以下为原文内容

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In today’s rapidly evolving technological landscape, the intersection of data and artificial intelligence (AI) has become a critical focus for organizations across industries. According to Foundry’s recent CIO Tech Poll, IT leaders have overwhelmingly placed AI-enabled solutions at the top of their investment list for 2024, with only 8% expressing no interest in generative AI. This surge in AI prioritization underscores the need for a deeper understanding of how data and AI can work together to drive innovation and business value.

To explore this crucial topic, we recently hosted a panel discussion featuring industry experts from Informatica, Immuta, and Dataiku. The panel brought their unique perspectives from real-life customer scenarios on the need for high-quality data, new regulations, and laying the right data foundations for everyone. The conversation centered around two key facets:

  1. How technology providers are ensuring intelligence is built into platforms to address security, privacy, governance, and policy control.
  2. How to enable customers to lead AI initiatives effectively by leveraging the power of their own data.

Panel:
Robin Sutara – Field CTO, Databricks
Conor Jensen – Dataiku, Field CTO
Rik Tamm-Daniels – Informatica, GVP Ecosystem and Technology, Informatica
Chris Brown – Immuta, Public Sector CTO

Let’s delve into the key insights shared by our esteemed panelists.

Leveraging AI for Data Management and Vice Versa

Rik Tamm-Daniels from Informatica highlighted the company’s approach to integrating AI into data management processes:

  • Incorporating generative AI to accelerate data management
  • Simplifying user interactions with data using natural language interfaces within an intelligent data warehouse
  • Creating enterprise-grade AI applications that integrate not only public data and AI models but also first-party data

This approach emphasizes the importance of a strong data foundation in unlocking the full potential of AI technologies.

Ensuring Data Security and Access Control

Chris Brown from Immuta focused on the critical aspect of data security:

  • Identifying and understanding the location of sensitive data across various storage systems
  • Creating rules to ensure only authorized personnel have access to specific data sets
  • Implementing automated policies for data engineering and report creation

A customer success story shared by Chris illustrated how organizations are leveraging solutions from Dataiku, Immuta, and Databricks to enhance their data engineering capabilities while maintaining strict governance.

Democratizing Data Access and Usage

Conor Jensen from Dataiku emphasized the importance of making data accessible to everyone in an organization:

  • Enabling all employees to leverage data across various use cases
  • Addressing the challenge of limited access to valuable data within platforms
  • Striking a balance between ease of use and risk management in data access

The Role of Metadata in AI Applications

The panelists agreed on the critical role of metadata in integrating different data assets with Large Language Models (LLMs). Ensuring the right data is input into AI systems is crucial for generating reliable and trustworthy outputs, reinforcing the “garbage in, garbage out” principle.

Balancing Innovation and Risk

Robin Sutara from Databricks touched on the impact of generative AI on people, processes, and change management:

  • The need for alignment with business outcomes
  • The distinction between data governance and AI governance
  • The importance of bringing in the right tools for data and AI governance

She concluded with a powerful message: “Build for the future, but don’t wait for the future.” The combined solutions from Databricks, Immuta, Informatica, and Dataiku empower organizations to adapt to evolving technologies without constant rebuilding, ensuring continuous empowerment of data consumers.

Conclusion

As organizations continue to navigate the complex landscape of data and AI, insights from industry leaders become invaluable. By focusing on strong data foundations, breaking down data silos, robust security measures, and accessible yet governed data practices, businesses can harness the full potential of AI while mitigating associated risks.

To gain deeper insights into this fascinating discussion, we encourage you to watch the full panel discussion.