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Lakehouse Architecture to Advance Security Analytics at the Department of State.pdf

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1、Lakehouse Architecture to Advance Security Analytics at the Department of State Tim AhrensBrendan BarsnessDatabricks2023Agenda1What is the Department of States Center for Analytics(CfA)2The Challenge3OrganizationalThe Response and Recommendations4TechnicalThe Response and RecommendationsUNCLASSIFIED

2、UNCLASSIFIEDCenter for AnalyticsWho We SupportWe empower employees across every bureau and over 200 missions,from working-level to the Secretary.Who We AreCfA is the Department of States enterprise data management and analytics capability.Led by the Chief Data Officer,we transform data into bold ins

3、ights that help make better management and foreign policy decisions.3UNCLASSIFIEDUNCLASSIFIEDWhat is State Department M/SS CfA?ANALYTICSDATA CULTUREDATA MANAGEMENTDATA GOVERNANCEAccelerate Decisions through AnalyticsCultivate a Data CultureEstablish Mission-Driven Data ManagementEnhance Enterprise D

4、ata GovernanceAnalyticsEnterprise Engagement&CommunicationsEnterprise Data ManagementTechnology Empower the Departments global workforce to utilize data by providing easy access to the Departments data assets,modern analytics tools,and customer service to enable their use.Recruit,train,and incentivi

5、ze a workforce andworkplace where data is routinely sought,valued,andfluently utilized for decision-making at all levelsand geographies.Implement technology solutions to effectively create,collect,store,protect,and share data across the Department,the interagency,and with the public.Enable oversight

6、 and coordination of Department data through effective stewardship,policies,process controls,and investment decisions that appropriately value data.UNCLASSIFIEDUNCLASSIFIED1_DAIS_Title_SlideThe Challenge*M-21-31 Improving the Federal Governments Investigative and Remediation Capabilities Related to

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本文主要介绍了美国国务院下属的Center for Analytics(CfA)如何通过建立企业数据管理和分析能力,应对联邦政府在网络安全事件日志记录方面的挑战。CfA由首席数据官领导,旨在将数据转化为大胆见解,以帮助做出更好的管理和外交政策决策。文章概述了CfA的组织架构、面临的挑战、以及提出的技术和组织响应建议。 技术上,面对M-21-31指令提出的详尽且具有指令性的日志记录要求,CfA提出了企业湖屋(Lakehouse)架构。该架构通过在各个云节点或数据节点上分布式处理数据,使国务院能够直接连接到集中的分析云,而不必将原始数据跨边界迁移,从而实现云中立存储解决方案。湖屋架构支持多云和多区域、长期数据保留、PB级别数据处理,并内置AI/ML功能以支持批量处理和近实时高级分析。 组织上,CfA的湖屋架构得到了利益相关者治理和政策的支持,以确保参与、实施和安全性。建议包括建立明确的职责划分、确保高级别管理层的支持、更新政策以支持联邦要求,并建立指导系统所有者和数据提供者的指南。 文中未直接引用具体数据,但提到了M-21-31指令要求日志记录的广度和持续时间要求,以及存储TB/天量数据的高成本问题。此外,还提到了湖屋架构的好处,如减少数据传输成本、降低数据重复、提高企业范围内可见性,并利用低成本云存储。
"如何提升国务院数据分析能力?" "湖屋架构如何改善网络安全分析?" 国务院数据分析中心的实践与挑战"
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