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보안 설계\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E모든 워크로드를 지원하는 고성능 인프라\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ESnowflake는 Summit 2026에서 이러한 과제를 해결하기 위한 새로운 기능들을 공개했습니다. 잘 보호되고 이해하기 쉬운 데이터에 에이전트가 적절한 수준으로 액세스할 수 있도록 지원하고, 빠른 실행이 가능한 속도를 제공함으로써 AI를 프로덕션 환경에 자신 있게 배포할 수 있게 합니다.\u003C/p\u003E\r\n\u003Ch2\u003EAI를 위한 신뢰할 수 있는 컨텍스트 계층\u003C/h2\u003E\r\n\u003Cp\u003EAI 에이전트의 성능은 결국 분석과 추론에 사용하는 데이터의 품질에 달려 있습니다. 에이전트가 쿼리 속도를 높이고 더 자율적인 작업을 수행할수록, 데이터 자산 환경 전반에서 일관된 비즈니스 로직과 정의를 갖추는 것이 성공의 핵심 요소가 됩니다. 예를 들어 '활성 고객(active customers)'이라는 지표는 BI 대시보드, Snowflake Cortex AI 에이전트, 분석가의 SQL 쿼리 중 어디에서 조회하든 동일한 값을 반환해야 합니다. 하지만 비즈니스 로직이 Snowflake 외부의 도구와 데이터 전반에 흩어져 있다면, 정의가 달라질 수 있습니다. 이러한 시맨틱 단절 문제는 신뢰를 저하시킬 뿐 아니라, 에이전틱 워크플로우가 늘어날수록 더욱 심화됩니다. \u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E\u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/horizon-context/\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Horizon 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Horizon Context의 기본 제공 커넥터는 쿼리 기록, dbt 모델, BI 로그에서 컨텍스트를 자동으로 추출해 조직의 축적된 지식을 활용하고 시맨틱 모델 구축을 가속화합니다.\u003C/p\u003E\r\n\u003Cp\u003E또한 \u003Cb\u003ESemantic Studio\u003C/b\u003E(프라이빗 프리뷰)와 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/semantic-view-autopilot/\"\u003E\u003Cb\u003ESnowflake Semantic View Autopilot\u003C/b\u003E\u003C/a\u003E(GA)을 사용해 메타데이터 보강을 자동화함으로써 컨텍스트 계층을 구축하고 유지하는 데 필요한 수작업을 줄일 수 있습니다. Snowflake CoCo는 SQL 생성 작업을 맡기든 더 높은 수준의 데이터 분석 작업을 맡기든, Universal Search를 사용해 관련 컨텍스트를 자동으로 검색합니다. Universal Search는 키워드와 시맨틱 검색을 결합한 방식으로, 인기도와 같은 신호를 반영해 결과를 정렬하고 액세스 제어 정책을 적용해 결과를 필터링합니다.\u003C/p\u003E\r\n\u003Cp\u003EHorizon Context는 Snowflake 외부에서도 거버넌스가 적용된 시맨틱 기반을 활용할 수 있도록 다음과 같이 다양한 Snowflake 기능을 활용합니다.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E기본 제공 커넥터: \u003C/b\u003EPostgreSQL, Microsoft SQL Server, Tableau, Microsoft Power BI, dbt와 같은 도구에 연결해 쿼리 로그, 인기도, 스키마 등 풍부한 컨텍스트를 다양한 소스에서 수집하고 하나의 검색 가능한 카탈로그로 통합합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E엔드투엔드 컬럼 수준 계보: \u003C/b\u003E계보는 데이터 자산이 서로 어떻게 연결되어 있는지 이해하는 데 있어 핵심 요소입니다. Horizon Context는 Snowflake와 외부 데이터베이스 쿼리 로그, BI 시스템, OpenLineage 피드에서 계보 정보를 추출하고 이를 하나로 연결해 완전한 엔드투엔드 계보 그래프를 생성합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EOpen Semantic Interchange(OSI) 네이티브 통합\u003C/b\u003E(프라이빗 프리뷰): 지표, 차원, 관계에 대한\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/open-semantic-interchanges-specs-finalized/\"\u003E 공급업체 중립적 사양\u003C/a\u003E을 제공하므로 Horizon Context에 정의된 비즈니스 로직을 별도의 변환 없이도 전체 데이터 생태계에서 읽고 이해할 수 있습니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003ESemantic Studio\u003C/b\u003E(프라이빗 프리뷰): SQL을 작성하지 않고도 시맨틱 뷰를 구축할 수 있는 시각적 모델링 인터페이스를 제공해 데이터 팀은 물론 비즈니스 분석가까지 거버넌스를 손쉽게 활용할 수 있습니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EXMLA Endpoint for Semantic Views powered by AtScale\u003C/b\u003E(프라이빗 프리뷰 예정): Power BI와 Excel을 시맨틱 계층에 직접 연결해, 엔터프라이즈 BI 사용자도 AI 에이전트와 동일한 거버넌스 기반 정의로 작업할 수 있도록 지원합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EAdvanced Semantics\u003C/b\u003E(프라이빗 프리뷰): 상세 수준(LOD) 계산, 구성 가능한 정의, 자동 쿼리 재작성을 지원하는 사용자 정의 구체화를 지원합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EHorizon Context에 대한 자세한 내용은 Snowflake 블로그 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/horizon-context-governed-context\"\u003E“Snowflake Horizon Context: AI, BI 및 앱을 위한 거버넌스 기반 컨텍스트 계층"\u003C/a\u003E에서 확인할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake는 Horizon Contex의 릴리스와 함께 Horizon Catalog를 고도화하며 이를 Snowflake 내부뿐 아니라 외부까지 포함하는 데이터 전반의 거버넌스를 위한 중앙 제어 플랫폼으로 강화했습니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/en/blog/snowflake-cowork-personal-work-agent\"\u003ESnowflake CoWork\u003C/a\u003E\u003C/b\u003E가 SQL에 능숙한 사용자에게만 국한하지 않고 모든 사용자가 정책, 분류, 액세스 제어를 쉽게 활용할 수 있도록 했다면,\u003Cb\u003E Intent-Driven Governance\u003C/b\u003E(프라이빗 프리뷰) 기능은 자연어 기반 템플릿을 활성 Horizon Catalog 정책으로 변환합니다. 이를 통해, 비즈니스 리더와 데이터 실무자는 Snowflake의 거버넌스 기본 구성 요소를 몰라도 거버넌스 의도를 승인할 수 있으며, Snowflake는 태그 기반 정책을 자동으로 적용합니다. 이 정책은 마스킹, 접근 제어, 데이터 품질을 포함해 기존 오브젝트는 물론 향후 생성되는 오브젝트까지 일관되게 적용됩니다. 또한 시스템은 지속적으로 정책의 변경(드리프트)를 감지하고, 현재 구성 상태를 승인된 정책 의도와 연결해 상세한 감사 리포트를 생성합니다. 아울러 \u003Cb\u003ESnowflake CoCo 스킬을 통한 에이전틱 거버넌스\u003C/b\u003E(GA)를 통해 사용자는 자연어 프롬프트로 서로 다른 리소스 전반에 정책을 적용하고, 버그를 수정하며, 민감 데이터를 모니터링할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003EHorizon Catalog는 이제 \u003Cb\u003E외부 엔진과의 안전한 전체 양방향 읽기 및 쓰기 액세스\u003C/b\u003E(GA)를 제공하며, Snowflake에서 정의한 정책을 Apache Iceberg™ REST 호환 엔진 전반으로 확장합니다. 또한 \u003Cb\u003EApache Iceberg REST Scan Planning API\u003C/b\u003E(퍼블릭 프리뷰) 지원을 통해 다양한 환경에서의 정교한 데이터 보호 정책 적용이 가능해졌습니다. 이러한 기능을 통해 고객은 처음부터 모든 엔진이 안전하게 액세스할 수 있는, 거버넌스가 적용된 단일 데이터 사본을 기반으로 작업할 수 있으며, 에이전틱 엔터프라이즈의 비즈니스 속도에 맞춰 운영 가능한 아키텍처를 제공함으로써 팀과 에이전트의 실행 속도를 높일 수 있습니다. Snowflake의 Interoperable Lakehouse를 통해 단일 데이터 기반으로 안전하게 표준화하는 방법에 대한 자세한 내용은 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"http://www.snowflake.com/en/blog/interoperable-lakehouse-architecture\"\u003E여기\u003C/a\u003E에서 확인하실 수 있습니다.\u003C/p\u003E\r\n\u003Ch2\u003E내장형 AI 에이전트 보안\u003C/h2\u003E\r\n\u003Cp\u003E기존의 액세스 제어는 알려진 역할, 예측 가능한 액세스 패턴, 감사 가능한 세션을 기반으로 작업하는 사람 중심 환경을 위해 설계되었습니다. 하지만 에이전트는 이 전제를 뒤집습니다. 에이전트는 머신 속도와 규모로 지속적으로 작동하며, 프롬프트를 통해 의도치 않거나 악의적인 방식으로 동작하도록 조작될 수 있습니다. 또한 오늘날 많은 플랫폼에서 에이전트는 검증 가능한 신원, 범위가 제한된 권한, 명확한 감사 추적을 갖추지 못하고 있습니다. 이는 프로덕션 배포를 가로막는 큰 장애물이 됩니다. 실제로 Snowflake의 보고서 \u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ko/lp/radical-roi-generative-ai/\"\u003E“2026 생성형 AI와 에이전트의 ROI”\u003C/a\u003E에서 응답자의 절반 이상(56%)이 거버넌스 및 규정 준수와 관련된 과제를 하나 이상 경험했다고 답했습니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake는 자율형 에이전트까지 제로 트러스트 원칙을 확장한, 목적에 맞게 설계된 에이전트 보안 모델로 이러한 과제에 정면으로 대응하고 있습니다. \u003Cb\u003EAgent Identity\u003C/b\u003E(퍼블릭 프리뷰)는 모든 에이전트가 프로덕션 환경에서 데이터에 액세스하기 전에 암호화 방식으로 검증된 ID를 부여합니다. 이 새로운 컨텍스트는 감사 가능성을 강화하고, 완전한 추적 체계를 구축하여, 금융 서비스, 헬스케어, 공공 부문처럼 규제가 엄격한 산업의 규정 준수 프레임워크가 요구하는 추적성 요건을 충족할 수 있도록 지원합니다.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"wistia_video":{"id":"wistia-video-15d098c0e5","title":{"id":"title","type":"heading1","lines":["신뢰할 수 있는 AI를 위한 기반 구축"],":type":"snowflake-site/components/title"},"wistiaVideoId":"pcs4yhs5wm","captionDescription":"Agent Identity는 감사 추적 기능을 제공하고, 실시간에 가까운 액세스 제안을 지원합니다. ","showVideoLength":true,"showRewatchButton":true,":type":"snowflake-site/components/wistia-video"},"blog_text_1581545899":{"id":"blog-text-06d179ea63","text":"\u003Cp\u003E이러한 문제를 해결하기 위해 설계된 제어 기능을 활용하면 에이전트 ID와 상호작용을 효과적으로 관리할 수 있으며, Snowflake의 네이티브 보안 기능을 기반으로 AI 에이전트와 앱을 더욱 자신 있게 확장할 수 있습니다. 이 기반은 AI 프로젝트를 지연시키는 주요 과제를 해결하기 위한 심층 방어 보안 스택으로 한층 강화됩니다.\u003C/p\u003E\r\n\u003Ch3\u003E에이전트를 위한 안전한 액세스\u003C/h3\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EAI Security Posture Management\u003C/b\u003E(퍼블릭 프리뷰)는 Snowflake Trust Center를 통해 제공되며, 에이전트 보안 상태를 지속적으로 모니터링하고, 에이전트 행동 전반에 걸쳐 이상 징후를 선제적으로 탐지합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003E데이터 자산 환경을 위한 엔터프라이즈급 심층 방어\u003C/h3\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EPrompt Injection Protection Phase 2\u003C/b\u003E(GA)는 LLM 기반 준실시간 탐지를 통해 제로데이 프롬프트 인젝션과 탈옥 시도를 감지합니다. 이는 엔터프라이즈 AI 보안 평가에서 자주 요구되는 기능입니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EData Movement Policies\u003C/b\u003E(프라이빗 프리뷰)는 전송을 시작한 도구와 관계없이, 에이전틱 워크플로우와 API 연결을 통한 무단 데이터 유출을 방지하는 플랫폼 수준 제어 기능을 제공합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EMulti-Party Approval\u003C/b\u003E(퍼블릭 프리뷰)은 고위험 작업 수행 전에 명시적 승인을 요구하는 'four-eyes' 권한 부여 체계를 제공합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EData ExfiltratioinTrust Center Package\u003C/b\u003E(프라이빗 프리뷰)와 \u003Cb\u003ERansomware Protection\u003C/b\u003E은 UI를 통한 과도한 데이터 다운로드, 내부 및 외부 스테이지로의 비정상적인 데이터 전송을 겨냥한 이상 감지 등 대규모 데이터 침해의 일반적인 벡터를 모니터링합니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003E에이전트에 대한 사용자 액세스 간소화\u003C/h3\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003EJust-in-Time User Provisioning\u003C/b\u003E과 \u003Cb\u003ERequest Access Workflow\u003C/b\u003E(둘 다 프라이빗 프리뷰)는 사용자 및 에이전트가 엑세스 권한을 부여받는 과정을 엄격히 제어하여, 불필요한 상시 권한(standing privilege)을 줄입니다.\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003ESnowflake AI 보안 기능 향상에 대한 자세한 내용은 Snowflake 블로그 \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/ko/blog/enterprise-ai-security/\" rel=\"nofollow noopener noreferrer\"\u003E“AI 시대의 속도에 대응하는 엔터프라이즈 보안 체계”\u003C/a\u003E를 참조하세요.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"blog_text_1147887412":{"id":"blog-text-bc8c4cff5a","text":"\u003Ch2\u003E거버넌스와 고성능을 동시에\u003C/h2\u003E\r\n\u003Cp\u003E에이전트는 지연을 용납하지 않습니다. 데이터 액세스 속도가 조금만 느려져도 자율형 에이전트가 수행할 수 있는 작업이 제한되며, 이로 인해 팀은 거버넌스가 적용된 플랫폼 대신 고성능을 위해 별도의 환경을 선택하게 됩니다. 이러한 우회 방식은 지연을 줄일 수는 있지만, 동시에 인프라 관리 부담을 증가시키고 거버넌스 리스크를 키우는 결과를 초래합니다.\u003C/p\u003E\r\n\u003Cp\u003ESnowflake 컴퓨팅 포트폴리오의 새로운 기능은 모든 AI 및 데이터 워크로드에 고성능을 제공하면서, 일관된 거버넌스를 유지하고 운영 부담을 크게 줄여 이러한 트레이드오프를 더 이상 고민할 필요 없는 문제로 만듭니다. 그 결과, 팀은 수동 유지 보수 작업 대신 보다 전략적인 업무에 집중할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E\u003Ca rel=\"nofollow noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/en/product/features/adaptive-compute/\"\u003ESnowflake Adaptive Compute\u003C/a\u003E\u003C/b\u003E(GA 예정)는 빠르게 변화하는 AI 환경에서, 성능, 사용 편의성, 확장성 등 핵심 운영 과제를 해결합니다. 특히 점점 다양해지고 예측이 어려워지는 워크로드 환경에서이 세 가지를 균형 있게 유지할 수 있도록 설계되었습니다. \u003C/p\u003E\r\n\u003Cp\u003EAdaptive Compute 기반으로 생성된 \u003Cb\u003EAdaptive Warehouses\u003C/b\u003E는 수동 사이징, 클러스터 관리, 용량 계획 없이도 수요에 따라 동적으로 조정되는 워크로드 인식 컴퓨팅을 제공합니다. Snowflake는 계정 내 공유 컴퓨팅 풀을 기준으로 리소스 할당, 규모 조정, 쿼리 라우팅을 처리합니다. 따라서 이전에는 별도의 튜닝 주기가 필요했던 구성 결정을 이제는 사람의 개입 없이 지속적으로 최적화할 수 있습니다. 이는 특히 여러 사업부에서 컴퓨팅을 관리하는 팀의 운영 오버헤드를 크게 줄일 수 있습니다. \u003C/p\u003E\r\n\u003Cp\u003E고성능은 여전히 핵심 강점입니다. Adaptive Compute는 최신 하드웨어와 성능 개선 사항을 반영하여, 다양한 워크로드에서 다음과 같이 표준 Snowflake 컴퓨팅(Gen1 및 Gen2) 대비 의미 있는 성능 향상(TPC-DS 및 내부 벤치마크 기준)을 보여줍니다.\u003Csup\u003E1\u003C/sup\u003E\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E탐색적 분석, 데이터 사이언스, 애드혹 분석과 같은 분석 워크로드 \u003Cb\u003E최대 1.6배 빨리 처리\u003C/b\u003E\u003C/li\u003E\r\n\u003Cli\u003E고동시성 운영 분석에서 \u003Cb\u003E최대 2.2배 높은 처리량\u003C/b\u003E(쿼리/시간)\u003C/li\u003E\r\n\u003Cli\u003E데이터 변환, 수집, 파이프라인 등 DML 비중이 높은 워크로드에서 \u003Cb\u003E최대 3.5배 빨리 실행\u003C/b\u003E\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-493d4b66f4","alt":"Adaptive Compute incorporates the latest hardware and performance enhancements, demonstrating meaningful performance gains.","lazyEnabled":true,"src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--002cde5f-e378-4be2-97fe-bcb8c4fa1ddd/adaptive-compute-performance.jpg?quality=85&preferwebp=true","height":"800","width":"3186","title":"업계 표준 벤치마크(TPC-DS)와 자체 벤치마크를 기반으로 Standard Gen1 인스턴스와 Adaptive Warehouse를 비교한 결과입니다. 측정은 2026년 5월 기준 고객에게 공개된 기능만을 사용해 실제 운영 환경에서 수행되었습니다.",":type":"snowflake-site/components/image"},"blog_text_1781740656":{"id":"blog-text-b7a95dfb0b","text":"\u003Cp\u003EAdaptive Compute의 차별화된 컴퓨팅 방식에 대한 자세한 내용은 Snowflake 블로그 \u003Ca href=\"https://www.snowflake.com/en/blog/adaptive-compute-performance/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E“Adaptive Compute, 워크로드에 맞춰 진화하는 고성능 컴퓨팅 제공”\u003C/a\u003E에서 확인해보세요.\u003C/p\u003E\r\n\u003Cp\u003E실시간에 가까운 데이터 최신성과 높은 분석 쿼리 성능을 동시에 요구하는 워크로드의 경우, \u003Cb\u003E\u003Ca rel=\"nofollow noopener noreferrer\" href=\"https://www.snowflake.com/ko/product/use-cases/interactive-analytics/\" target=\"_blank\"\u003EInteractive Analytics\u003C/a\u003E\u003C/b\u003E는 이전에는 별도 인프라 스택이 필요했던 스트리밍 기능을 제공합니다. \u003Cb\u003EStreaming Ingestion\u003C/b\u003E(프라이빗 프리뷰)은 지속적으로 수집되는 데이터를 Interactive Table로 가져와 Snowflake의 거버넌스 범위 내에서 서브초 단위의 최신성과 1,000+ QPS 동시 처리 성능을 제공합니다.\u003Csup\u003E2\u003C/sup\u003E\u003C/p\u003E\r\n\u003Cp\u003E두 가지 추가 기능은 이러한 성능과 단순성을 트랜잭션 워크로드로 확장합니다. \u003Cb\u003EPostgres Data Mirroring\u003C/b\u003E(퍼블릭 프리뷰 예정)은 \u003Ca href=\"https://www.snowflake.com/ko/product/features/postgres/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Postgres\u003C/a\u003E의 데이터를 \u003Ca href=\"https://www.snowflake.com/ko/product/analytics/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Analytics\u003C/a\u003E로 자동 복제해, 기존에 두 시스템을 연결하기 위해 필요했던 복잡한 ETL과 연결 코드를 제거합니다. CoCo, Snowsight UI 또는 SQL을 통해 몇 분 안에 설정을 완료할 수 있으며, 설정만 해두면 데이터 흐름이 매끄럽게 이어집니다. 또한 \u003Cb\u003E\u003Ca href=\"https://docs.snowflake.com/ko/user-guide/tables-hybrid\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EHybrid Table\u003C/a\u003E\u003C/b\u003E은 내부 벤치마크 기준 최대 8배의 처리량 향상\u003Csup\u003E3\u003C/sup\u003E, 10배 빠른 배치 쓰기\u003Csup\u003E4\u003C/sup\u003E, 평균 15%의 비용 효율 개선\u003Csup\u003E5\u003C/sup\u003E을 달성했습니다. 이러한 혁신을 통해 고객은 별도의 데이터베이스를 추가하지 않고도 더 까다로운 워크로드를 처리할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E이러한 기능을 대규모로 운영하는 조직을 위해, \u003Ca href=\"https://www.snowflake.com/ko/product/use-cases/well-architected-framework/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E\u003Cb\u003ESnowflake Well-Architected Framework (WAF)\u003C/b\u003E\u003C/a\u003E\u003Cb\u003E\u003C/b\u003E는 데이터 및 AI 워크로드를 위한 통합 엔터프라이즈급 운영 모델을 지원하도록 모범 사례와 가드레일을 표준화합니다. 팀 구성원은 이제 CoCo를 통해 자연어 기반으로 WAF에 액세스할 수 있습니다. 플랫폼의 모든 구성 영역에 대한 전문 지식 없이도 프레임워크의 핵심 원칙에 맞춰 아키텍처를 평가하고, 격차를 파악하며, 모범 사례를 구현할 수 있습니다.\u003C/p\u003E\r\n\u003Ch2\u003E엔터프라이즈 AI 배포를 자신 있게\u003C/h2\u003E\r\n\u003Cp\u003ESnowflake의 새로운 기능과 향상된 역량은 컨텍스트, 거버넌스, 보안을 유기적으로 연결하는 접근 방식의 가치를 보여줍니다. 이는 확장 가능한 고성능을 기반으로, 변화하는 AI 워크로드의 특성에 지능적으로 대응할 수 있도록 설계되었습니다. 이러한 아키텍처를 통해 엔터프라이즈 AI는 제한된 파일럿 단계를 넘어, 조직이 신뢰하고 운영에 활용할 수 있는 시스템으로 확장됩니다.\u003C/p\u003E\r\n\u003Cp\u003E더 자세한 내용은 아래 리소스를 참고하세요.\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/en/product/features/horizon-context/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EHorizon Context\u003C/a\u003E와 \u003Ca href=\"https://www.snowflake.com/ko/product/features/horizon/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EHorizon Catalog\u003C/a\u003E의 다른 개선 사항 살펴보기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E신뢰할 수 있는 데이터 에이전트에 \u003Ca href=\"https://www.snowflake.com/ko/blog/agent-context-layer-trustworthy-data-agents/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E컨텍스트가 중요한 이유\u003C/a\u003E 알아보기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ko/why-snowflake/snowflake-security-hub/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Security Hub\u003C/a\u003E 및 \u003Ca href=\"https://trust.snowflake.com/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ETrust Center\u003C/a\u003E에서 AI 보안에 대해 알아보기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/en/product/features/adaptive-compute/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EAdaptive Compute 페이지\u003C/a\u003E를 확인하고, 6월 3일 수요일 12:30 p.m.(PDT)에 열리는 \u003Ca href=\"https://reg.snowflake.com/flow/snowflake/summit26/sessions/page/catalog/session/1773336025108001T9OW\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Summit 2026 Adaptive Warehouse 세션\u003C/a\u003E에 참석하기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E“\u003Ca href=\"https://www.snowflake.com/en/resources/ebook/essential-guide-transactional-analytical-hybrid-data/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E트랜잭션, 분석 및 하이브리드 데이터 필수 가이드\u003C/a\u003E”에서 워크로드 통합의 가치 살펴보기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003Cli\u003E\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ko/product/use-cases/well-architected-framework/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003EWell-Architected Framework\u003C/a\u003E 상세 정보 확인하기\u003C/p\u003E\r\n\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n\u003Cp\u003E\u003Csup\u003E1 \u003C/sup\u003E업계 표준(\u003Ca href=\"https://docs.snowflake.com/ko/user-guide/sample-data-tpcds\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ETPC-DS\u003C/a\u003E) 및 자체 벤치마크를 조합해 측정했으며, Standard Gen1 인스턴스와 Adaptive Warehouse를 비교했습니다. 2026년 5월 기준, 공개적으로 제공되는 고객용 기능만 사용해 프로덕션 배포 환경에서 측정한 결과입니다. \u003C/p\u003E\r\n\u003Cp\u003E\u003Csup\u003E2\u003C/sup\u003E 성능 결과는 2026년 1월 소형 인터랙티브 웨어하우스 구성에서 측정한 \u003Ca href=\"https://docs.snowflake.com/ko/user-guide/interactive#interactive-table-performance-considerations\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E인터랙티브 분석 워크로드\u003C/a\u003E 기준입니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Csup\u003E3\u003C/sup\u003E Gen2 XS 웨어하우스에서 100% 읽기 워크로드를 대상으로 Yahoo Cloud Serving Benchmark(YCSB)를 실행한 결과입니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Csup\u003E4\u003C/sup\u003E 2X-Large 웨어하우스를 사용해 Hybrid Table에 데이터 50GB를 로드하는 내부 벤치마크 기준입니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Csup\u003E5\u003C/sup\u003E Snowflake가 고객 전반에 걸친 평균 비용 절감 효과를 추정한 결과로, 2026년 2월 실제 운영 환경의 크레딧 사용량을 기반으로 측정되었습니다.\u003C/p\u003E\r\n\u003Cp\u003E \u003C/p\u003E\r\n\u003Cp\u003E\u003Ci\u003E본 콘텐츠에는 향후 제품 제공에 대한 미래 전망 진술이 포함되어 있으며, 이는 제품 제공에 대한 약속이 아닙니다. 실제 결과 및 제공 내용은 달라질 수 있으며, 알려진 위험과 알려지지 않은 위험 및 불확실성의 영향을 받을 수 있습니다. 보다 자세한 내용은 최신 10-Q를 참조하세요.\u003C/i\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"premium_content_bann":{"id":"premium-content-banner-1c4dae1e99","contentHeadline":"Inside Summit 26","contentDescription":"Snowflake Summit 2026에서 발표된 주요 발표 내용과 기능 개선 사항, 혁신에 대해 자세히 살펴보세요.","showImage":false,"buttons_container":{"id":"container-90520b8e00","layout":"SIMPLE",":type":"snowflake-site/components/button/buttons-container",":items":{"button":{"id":"button-a851a0e4fd","showOutboundIcon":false,"buttonLink":{"valid":true,"attributes":{"target":"_blank"},"url":"https://www.snowflake.com/en/blog/summit-26/"},"linkTargetContentType":"GENERIC","linkType":"SNOWFLAKE_EXTERNAL",":type":"snowflake-site/components/button","text":"지금 방문하기","appliedCssClassNames":"snowflake-button-primary snowflake-button-blue 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