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프로젝트의 열쇠"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"]},"responsivegrid_content":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"image":"aem-GridColumn aem-GridColumn--default--12","blog_text":"aem-GridColumn aem-GridColumn--default--12","blog_text_1599198641":"aem-GridColumn aem-GridColumn--default--12","blog_text_731223707":"aem-GridColumn aem-GridColumn--default--12","quote_item":"aem-GridColumn aem-GridColumn--default--12"},"columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-8253d422a7","text":"\u003Cp\u003E개인정보 보호 기준이 계속 진화함에 따라 기업은 데이터 협업을 제공하는 기회를 포착하면서도 데이터 사용에 대한 윤리적 표준을 유지해야 하는 이중 과제에 직면하고 있습니다. 그래서 필요한 것이 바로 데이터 클린룸입니다. 개인정보 보호를 강화하는 솔루션인 데이터 클린룸을 사용하는 조직은 규정 준수를 훼손하지 않고 귀중한 인사이트를 공유할 수 있습니다.* 데이터 클린룸이 생소하시다면 최근 블로그 게시물 \u003Ca href=\"https://www.snowflake.com/ko/blog/data-clean-rooms-privacy-collaboration/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E‘Data Clean Room: 개인정보 보호 우선 협업에 대해 알아야 할 사항’\u003C/a\u003E을 살펴보시기 바랍니다.\u003C/p\u003E\r\n\u003Cp\u003E데이터 클린룸의 잠재력은 엄청나지만, 이를 성공적으로 구현하는 일은 여느 엔터프라이즈 기술 프로젝트와 마찬가지로 매우 복잡할 수 있습니다. 따라서 규제 정책을 탐색하고 기술 요구 사항을 해결하는 과정에서 프로젝트가 일시 중지되거나 실패로 끝나는 경우가 비일비재합니다. 하지만 좋은 소식은 이러한 난관에도 불구하고, 클린룸을 통해 데이터 협업을 마스터하는 기업들은 상당한 경쟁 우위를 확보할 수 있다는 것입니다.\u003C/p\u003E\r\n\u003Cp\u003E그렇다면 이러한 데이터 협업 이니셔티브가 실패로 끝나는 이유는 무엇이고, 이를 성공적으로 이끌기 위해서는 어떻게 해야할까요? 본 게시물에서는 이 질문에 대한 해답으로서, 데이터 협업 이니셔티브가 공통적으로 직면하는 6가지 과제와 이를 극복할 수 있는 실행가능한 전략을 알아보도록 합니다.  \u003C/p\u003E\r\n\u003Ch2\u003E규정 준수\u003C/h2\u003E\r\n\u003Cp\u003E개인정보 보호법 및 규제 프레임워크의 준수 여부는 데이터 협업의 최대 장벽인 경우가 많습니다. 조직은 내규, 산업 규제(예: 미국 HIPAA, FCRA) 및 정부 의무 규정(예: GDPR, CCPA) 등 다양한 계층에 걸쳐 규정 준수를 관리해야 합니다. 특히 개인정보 보호법이 지속적으로 진화하고 있는 상황에서 협업 파트너까지 더해지면 한층 복잡해집니다.\u003C/p\u003E\r\n\u003Cp\u003E이러한 과제들을 해결하기 위해서는 프로젝트 초기에 법무 팀과 협력하여 잠재적 위험을 파악해 조기에 해결하는 것이 좋습니다. 또한, 조직 내 팀들의 데이터 사용 정책을 일치시키고 조달 팀을 통해 계약을 체결하도록 해야 합니다. 이러한 초기 작업을 거치면서 향후 협업을 위한 반복 가능한 프레임워크 및 프로세스를 구축할 수 있습니다.  \u003C/p\u003E\r\n\u003Cp\u003E동의 관리 및 데이터 스토리지 전략은 데이터 협업에서 규정 준수 유지와 마찬가지로 중요합니다. 데이터를 수집하는 과정이 투명하도록 보장하고 각 소비자가 제공한 기본 설정과 권한 내용을 존중해야 합니다. 소비자의 동의는 성공적인 협업을 위한 핵심 요소입니다. 또한, 추후 규정 준수 관리를 간소화하기 위해 데이터 출처를 철저히 추적하고, 데이터 수집 방법 및 위치, 승인된 데이터의 사용량 범위에 대한 기록을 유지해야 합니다.\u003C/p\u003E\r\n\u003Ch2\u003E거버넌스\u003C/h2\u003E\r\n\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ko/blog/privacy-first-marketing-strategy/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E강력한 데이터 거버넌스 없이는 규정 준수가 불가능합니다\u003C/a\u003E. 거버넌스는 본질적으로, 데이터 액세스와 사용 정책을 시행하는 것입니다. 그러나 오늘날의 복잡한 데이터 생태계에서는 정보가 여러 시스템과 플랫폼에 흩어져 있는 경우가 많기 때문에 거버넌스를 운영하는 것은 중요한 과제가 될 수 있습니다. 새로운 데이터 사본이 만들어질  때마다 위험이 추가됩니다. \u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"image":{"id":"image-9e9f24768c","height":"367","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--7735f707-9a7d-4ad3-b2aa-980c4cf35315/dcr-governancediagram.png?preferwebp=true&quality=85","alt":"Diagram showing how a governed Customer 360 approach allows a data clean room app access to consented data.","lazyEnabled":true,"width":"512",":type":"snowflake-site/components/image"},"blog_text_731223707":{"id":"blog-text-b84f69eb05","text":"\u003Cp\u003E다행히 데이터 플랫폼 기술의 발전으로 이제는 통합 거버넌스 솔루션이 제공되기 때문에 시스템 간에 데이터를 이동하거나 복제할 필요가 없습니다. 이러한 도구를 사용하면 생태계 내에서 직접 안전하게 협업할 수 있어 거버넌스를 단순화하고 위험을 줄일 수 있습니다. 예를 들어, 거버넌스 정책을 적용하여 마케팅 담당자와 분석가의 데이터 액세스와 데이터 사용을 제어할 수 있습니다. 또한, 거버넌스를 단일 팀에 맡기기보다는 전반적인 비즈니스 운영에 맞게 거버넌스를 적용하면 거버넌스로 인해 병목 현상이 발생하는 상황을 피할 수 있습니다. \u003C/p\u003E\r\n\u003Ch2\u003E전략\u003C/h2\u003E\r\n\u003Cp\u003E기술만으로는 결코 프로젝트의 성공을 보장할 수 없으며, 데이터 클린룸도 예외는 아닙니다. 비즈니스 팀과 기술 팀이 협력하는 견고하고 정교한 전략이 꼭 필요합니다. 그러한 전략이 없으면 협업이 버겁게 느껴질 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E이러한 과제를 극복하기 위해 조직은 작은 성과들을 달성하여 자신감을 쌓아가면서 더 큰 기회를 위한 추진력을 만들어가는 단계적인 접근 방식이 필요합니다.  \u003C/p\u003E\r\n\u003Cp\u003E그리고 협업 파트너와 함께 명확한 사용 사례부터 시작하세요. 광고주의 경우에는 측정이 첫 번째 선택하는 사용 사례인 경우가 많습니다. 광고 지출 및 유료 미디어 전략을 최적화하기 위해서는 캠페인의 효과를 이해하는 것이 중요하기 때문입니다. 광고주는 타깃 잠재 고객과 연계된 강력한 퍼스트 파티 데이터 세트를 보유한 미디어 소유자를 식별함으로써 귀중한 인사이트를 얻을 수 있습니다.\u003C/p\u003E\r\n\u003Ch2\u003E기술\u003C/h2\u003E\r\n\u003Cp\u003E안전하고 확장 가능한 기술 인프라는 모든 데이터 협업 이니셔티브에 필수적입니다. 데이터 역량을 확장해야 하는 조직은 자체 솔루션을 구축하거나 기존 기술을 구매하는 것 중 하나를 선택해야 하는 경우가 많습니다. 그러나 암호화 및 익명화 같은 개인정보 보호 강화 기술(PET)을 내장하는 데 따른 복잡성으로 인해 사내 개발은 시간과 리소스를 매우 많이 소모할 수 있습니다. 전문 지식과 시간적 여유가 있는 조직이라도 자체적으로 기술을 구축하는 데 소극적일 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E문제는 여기서 끝나지 않습니다. 협업을 실현하려면 보다 광범위한 데이터 솔루션 생태계를 통합해야 합니다. 여기에는 자사 데이터 세트를 서드 파티 데이터로 보강하거나, 유료 미디어 생태계 내에서 PII를 노출하거나 데이터를 활성화하지 않고 여러 ID 공급업체와 협력하여 데이터 세트를 매칭하는 작업이 포함될 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E대부분의 조직에서는 최신 플랫폼을 통해 기존 기능을 활용하는 것이 최적의 방안입니다. 데이터 클라우드 공급자는 개인정보 보호, 보안 및 거버넌스 제어를 통합하여 안전하고 규정을 준수하는 협업에 대한 엔터프라이즈의 요구를 충족할 수 있도록 지원합니다. 조직의 장기적인 전략에 부합하는 솔루션을 보유한 공급업체는 협업, 데이터 보강 및 실행성을 위한 원활한 생태계를 보장할 수 있습니다.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-8078f207ec","alignment":"left","layout":"card","quoteSourceName":"Jon Regan","quoteSourceTitle":"Vice President, Clean Room Product Owner, Merkle","showQuoteIcon":true,"quote":"많은 마케팅 팀들은 자사의 퍼스트 파티 데이터가 귀중한 자산이라는 것을 잘 알고 있지만 동시에 고객의 개인정보 보호를 책임져야하는 의무도 안고 있습니다. 따라서 이상적인 해결책은 안전한 데이터 환경을 활용하는 것입니다. 기업들은 내부에서 PII 데이터를 해싱(hashing)하거나 익명화하는 방법으로 외부 파트너와 협력하여 규정을 준수하고 데이터 유출의 위험 없이 귀중한 인사이트를 얻을 수 있습니다.\"","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_1599198641":{"id":"blog-text-dad7198cca","text":"\u003Ch2\u003E상호운용성\u003C/h2\u003E\r\n\u003Cp\u003E상호운용성은 클라우드 기술, 리전, 데이터 스토리지 및 형식, ID 등을 아우르는 데이터 협업 분야에서 아주 뜨거운 주제입니다. 조직은 스스로 선택을 내리면서도 다른 의사 결정을 내린 이들과 제약없이 협업할 수 있는 유연성을 원합니다. \u003C/p\u003E\r\n\u003Cp\u003E클라우드 인프라 관점에서 보면, 사용량은 파편화 양상을 띠고 있으며 AWS, Google Cloud, Microsoft Azure 클라우드가 시장 전반을 지배하고 있는 상황입니다. 이러한 파편화는 협업 상에 문제를 초래합니다. 협업은 공통 키를 통해 데이터 세트를 안전하게 매칭하여 시작하는 경우가 많으며, 솔루션은 저마다 다른 장단점을 갖고 있습니다. 또한, 데이터 클린룸 기술 간의 상호운용성은 다음과 같은 또 다른 과제를 초래합니다. 즉, 두 조직이 서로 다른 DCR 플랫폼을 선택하면 어떻게 되는지, DCR 플랫폼이 상이해도 안전하고 효과적인 협업이 이뤄질 수 있는지 고민해야 합니다.\u003C/p\u003E\r\n\u003Cp\u003E솔루션 공급자는 지배적인 단일 솔루션 존재하지 않는다는 사실을 점점 더 인식하게 될 것이며 파편화는 계속해서 중대한 과제로 작용할 것입니다. 상호운용성은 여러 솔루션이 공존할 수 있도록 지원하는 핵심 요소입니다. 조직은 유연성을 우선시하고 기술, 아이덴티티, 클라우드 전반에서 상호운용성을 높이는 공급업체를 선정합니다. 이러한 접근 방식은 진화하는 생태계에 적응하면서 협업 기회를 최적화합니다.\u003C/p\u003E\r\n\u003Ch2\u003E숙련도(Skills)\u003C/h2\u003E\r\n\u003Cp\u003E전통적으로 데이터 클린룸은 데이터 분석가와 데이터 사이언티스트를 염두에 두고 구축되었기 때문에 고급 기술에 대한 전문 지식이 필요했습니다. 이러한 접근 방식은 처음에는 합리적이었지만, 기술 리소스가 부족한 조직이나 공동 작업자의 경우 접근성을 크게 제한했습니다. 그 결과, 협업 기회 격차가 확대되었습니다.\u003C/p\u003E\r\n\u003Cp\u003E진정한 기회는 기술 격차를 해소하여 모든 사람이 데이터 클린룸에 액세스할 수 있도록 만드는 데 있습니다. 최신 데이터 클린룸 플랫폼은 진화하고 있으며, 기술 사용자를 위한 코드 기반 환경이나 비즈니스 사용자를 위한 노코드 기반 인터페이스 등 자신의 경험에 가장 적합한 인터페이스를 선택할 수 있는 유연성을 제공합니다.\u003C/p\u003E\r\n\u003Ch2\u003ESnowflake Data Clean Rooms: 안전하고 확장 가능한 데이터 협업 지원\u003C/h2\u003E\r\n\u003Cp\u003ESnowflake AI 데이터 클라우드의 신뢰할 수 있는 인프라를 기반으로 구축된 \u003Ca href=\"https://www.snowflake.com/ko/product/features/data-clean-rooms/?utm_cta=website-blog-why-data-collaboration-projects-fail\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Data Clean Rooms\u003C/a\u003E는 데이터 협업과 관련된 일반적인 과제를 해결하는 포괄적인 솔루션을 제공합니다. 그 방법은 다음과 같습니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E규정 준수:\u003C/b\u003E AI 데이터 클라우드를 중심으로 하는 Snowflake Data Clean Rooms는 규정 준수, 보안 및 개인정보 보호에 대한 포괄적인 솔루션을 조직에 제공합니다. Snowflake Horizon은 조직이 내부 정책, 산업 규정, 정부 지시에 원활하게 부합하도록 설계된 통합 기능 세트에 액세스할 수 있도록 지원합니다. \u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E거버넌스: \u003C/b\u003ESnowflake의 정교한 거버넌스 모델은 데이터 세트 전반에 걸쳐 데이터 사용량 정책을 시행하여 시스템 간에 분산된 데이터를 관리하는 데 따르는 운영 복잡성을 줄이고 보안 및 개인정보 보호를 엄격하게 제어합니다. 또한, Snowflake는 시스템 간에 데이터를 이동하거나 복제할 필요가 없습니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E기술: \u003C/b\u003ESnowflake는 AI 데이터 클라우드의 확장성을 고급 개인정보 보호 강화 기능과 결합하여 가장 복잡한 협업 사용 사례의 요구 사항을 충족하는 인프라를 제공합니다. 일부 대안과 달리 Snowflake는 데이터를 판매하거나 미디어를 소유하지 않고 중립적인 솔루션을 제공하기 때문에 신뢰성, 투명성 및 데이터 처리의 공정성을 보장할 수 있습니다. \u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E상호운용성: \u003C/b\u003ESnowflake의 기능을 통해 조직은 AWS, Google Cloud, Microsoft Azure 등 여러 클라우드와 리전에 걸쳐 원활하게 협업할 수 있습니다. Snowflake 플랫폼의 크로스 클라우드 기능은 공급업체 종속을 제거하여 조직이 파트너십을 확장할 수 있도록 지원합니다. Snowflake의 고객이 아닌 파트너도 Snowflake Data Clean Rooms(DCR)를 통해 원활하게 연결할 수 있어 혁신과 성장을 촉진하는 진정한 협업 생태계를 구축할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E숙련도: \u003C/b\u003ESnowflake Data Clean Rooms는 조직 내 기술 숙련도 차이를 인식하고 기술 전문가 및 비즈니스 사용자 모두를 지원하도록 설계되었습니다. 이러한 Snowflake Data Clean Rooms는 직관적인 인터페이스를 통해 데이터 협업의 진입 장벽을 낮추고 있습니다. Snowflake는 기술 숙련도 격차를 해소함으로써 기술적 제약 조건이 자주 적용되는 영역의 접근성을 촉진합니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003E전략: \u003C/b\u003ESnowflake는 전략을 우선시하는 데이터 협업 접근 방식을 지향합니다. 이 전략의 핵심은 관리가 용이한 소규모 프로젝트로 시작하여 팀의 경험과 자신감이 점차 쌓여가면서 빠르게 확장해 나가는 것입니다. Snowflake는 사전 라이선스 수수료 없이 기업이 최소한의 위험으로 파트너십을 탐색하고 확장할 수 있도록 지원합니다. \u003C/p\u003E\r\n\u003Cp\u003E최고의 퍼블리셔와 산업 리더가 신뢰하는 Snowflake Data Clean Rooms는 중립적이고 개인정보를 보호하고 구현이 용이한 데이터 협업 환경을 제공합니다.\u003C/p\u003E\r\n\u003Ch2\u003E고객 사례 집중 조명\u003C/h2\u003E\r\n\u003Cp\u003E인기 온라인 구직 플랫폼 Indeed는 캠페인 성과 측정을 개선하기 위해 Snowflake Data Clean Rooms를 선택하여, 최적화 노력에 드는 수고를 크게 줄이고 여러 협업 파트너와의 프로세스를 원활하게 복제하는 성과를 올렸습니다. Indeed가 제시하는 데이터 협업 이니셔티브 시작 시 권장 사항을 \u003Ca href=\"https://www.snowflake.com/webinars/how-indeed-uses-snowflake-data-clean-rooms-to-optimize-marketing-spend-with-privacy-and-transparency/?utm_cta=website-blog-why-data-collaboration-projects-fail\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E확인하세요\u003C/a\u003E.\u003C/p\u003E\r\n\u003Cp\u003E더 많은 정보가 필요하신가요? 그렇다면 ‘\u003Ca href=\"https://www.snowflake.com/resource/the-essential-guide-to-secure-data-collaboration-for-advertisers/?utm_cta=website-blog-why-data-collaboration-projects-fail\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E광고주를 위한 안전한 데이터 협업 필수 가이드\u003C/a\u003E(영문)’를 다운로드하고 안전하고 개인정보 보호를 우선하는 협업을 준비하세요.\u003C/p\u003E\r\n\u003Cp\u003E개인화된 지침이 필요한가요? 그렇다면 \u003Ca href=\"https://www.snowflake.com/en/contact-sales/?utm_cta=website-blog-why-data-collaboration-projects-fail\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003E영업 팀에 문의하세요\u003C/a\u003E. 데이터 협업 이니셔티브를 자신 있게 시작할 수 있도록 도와드릴 것입니다.\u003C/p\u003E\r\n\u003Cp\u003E\u003Ci\u003E* DCR은 주요한 기술 역량 강화 요소이지만, 본질적으로는 규정 준수 또는 개인정보 보호를 자체적으로 보장하지는 않습니다. 데이터 클린룸을 효과적으로 사용하려면 개인정보 보호 표준을 충족하기 위한 보다 광범위한 관행과 정책 그리고 책임 있는 의사 결정 프로세스가 필요합니다. 이러한 요소들이 없으면 클린룸의 기능에 관계없이 개인정보 보호 문제로 이어질 수 있는 실책이 발생할 가능성이 존재합니다.\u003C/i\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","image","blog_text_731223707","quote_item","blog_text_1599198641"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"premium_content_bann":"aem-GridColumn aem-GridColumn--default--12"},"columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"premium_content_bann":{"id":"premium-content-banner-e3bb313346","contentEyebrow":"eBook","contentHeadline":"광고주를 위한 안전한 데이터 협업 필수 가이드(영문)","contentDescription":"개인정보 보호를 우선하는 데이터 클린룸을 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