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Drobau"}},{"authorImage":{"id":"image-c924ac36e9","height":"512","lazyEnabled":true,"src":"/adobe/dynamicmedia/deliver/dm-aid--308d8981-6213-4584-8c66-3a4241ae1824/sem-sergunin.png?quality=85&preferwebp=true","isLcpImage":false,"width":"512",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-51e511ab19","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/sem-sergunin/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Sem Sergunin"}}],"image":{"id":"image-f17ebd2cb4","alt":"Close up of a man's hands typing","height":"720","lazyEnabled":true,"src":"/adobe/dynamicmedia/deliver/dm-aid--c2786592-e9c5-4b10-b60d-a843bf930513/blog-2-snowflake-intelligence-for-retail-%252B-consumer-goods-blog4-aem-1680x720.jpg?quality=85&preferwebp=true","isLcpImage":false,"width":"1680",":type":"snowflake-site/components/image"},"timeToRead":"7","publicationDate":"OCT 23, 2026","tag":{"tagText":"소매 및 소비재","tagColor":"#29B5E8"},"title":{"lines":["Brilliant Earth가 Snowflake와 Posit으로 데이터 민주화를 실현하는 방법"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"]},"responsivegrid_content":{"columnCount":12,"columnClassNames":{"blog_text":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-dc4850da8e","text":"\u003Cp\u003E탄탄한 이커머스 입지를 바탕으로 미국 내 쇼룸 네트워크를 넓혀 가고 있는 럭셔리 파인 주얼리 및 약혼반지 브랜드 Brilliant Earth는 매일 방대한 다이아몬드 재고의 가격을 자동으로 재책정합니다. 이 가격 모델은 Snowflake 내부에서 직접 실행됩니다. 애초에 Brilliant Earth가 Snowflake를 도입한 계기가 바로 이 자동화 기능이었습니다.\u003C/p\u003E\r\n\u003Cp\u003E이 자동화의 성공으로 비즈니스의 다른 영역에 대한 기대치도 높아졌습니다. Brilliant Earth가 여러 채널로 사업을 확장하면서 인사이트에 대한 수요는 기존 보고 방식이 감당할 수 있는 속도보다 더 빠르게 늘었습니다. 공들여 만든 주간 데이터 사이언스 보고서는 특정 시점의 상황을 담아냈지만, 팀은 제공 속도에서 기회를 발견했습니다. 회사 전반의 의사 결정권자가 신뢰할 수 있는 동일한 데이터에 셀프서비스로 직접 액세스할 수 있다면 어떨까요?\u003C/p\u003E\r\n\u003Cp\u003E"Brilliant Earth에는 이미 매우 유능한 데이터 사이언스 팀과 거버넌스가 잘 갖춰진 데이터가 있었습니다."라고 Posit의 시니어 솔루션 어드바이저인 Natallia Drobau는 말했습니다. "기회는 이 팀의 영향력을 넓혀, 모델과 인사이트가 단일 보고 채널에만 머무르지 않고 비즈니스 전반의 의사 결정을 뒷받침하도록 하는 데 있었습니다."\u003C/p\u003E\r\n\u003Cp\u003EBrilliant Earth의 분석 및 데이터 사이언스 담당 시니어 디렉터인 Matthias Mueller는 바로 이러한 내부 인재가 회사의 접근 방식을 바꿔야 하는 이유라고 보았습니다. "Brilliant Earth에는 놀라운 인재들이 있습니다. 제가 함께 일해 본 사람 중 최고의 인재들이 이곳에 있습니다."라고 Mueller는 말했습니다. "결국 이 모든 인재의 역량을 끌어내기 위해 사람들을 거버넌스가 적용된 하나의 생태계와 플랫폼으로 모으는 작업이었습니다."\u003C/p\u003E\r\n\u003Cp\u003E데이터 사이언스와 실시간 실행 사이의 격차를 해소하기 위해 Brilliant Earth는 Snowflake와 Posit을 선택했습니다. Posit은 RStudio, Shiny, Quarto 등 널리 사용되는 오픈소스 데이터 사이언스 도구와 Python 및 R로 데이터 사이언스 작업을 구축, 게시, 공유하기 위한 엔터프라이즈 플랫폼인 Posit Team을 개발한 소프트웨어 회사입니다. Brilliant Earth가 Snowflake 내부에 Posit을 네이티브로 배포해, 요청받은 보고서를 처리하던 중앙 분석 조직을 셀프서비스 데이터 제품을 전략적으로 구축하는 조직으로 어떻게 바꾸었는지 살펴보겠습니다.\u003C/p\u003E\r\n\u003Ch3\u003E인프라 수준에서 거버넌스 병목 현상 제거\u003C/h3\u003E\r\n\u003Cp\u003E많은 리테일 엔터프라이즈에서는 팀마다 고립된 도구를 따로 도입하면서 데이터 민주화가 정체됩니다. 그 결과 보고서 내용이 서로 엇갈리고, IT 부서는 관리에 큰 어려움을 겪습니다.\u003C/p\u003E\r\n\u003Cp\u003EBrilliant Earth는 Snowpark Container Services에서 실행되는 Snowflake Native App으로 Posit Team을 설치하여 이 거버넌스 딜레마를 해결했습니다. 유지 관리와 감독이 필요한 보안 프로토콜을 중복으로 운영하는 별도 서버를 두는 대신, Brilliant Earth는 Posit을 Snowflake 환경에 직접 통합했습니다.\u003C/p\u003E\r\n\u003Cp\u003E이제 사용자 프로비저닝은 완전히 자동화되었습니다. 직원이 IT 티켓팅 시스템에서 타일을 클릭하여 Posit 액세스를 요청합니다. 요청자의 관리자와 분석 팀이 승인하면 시스템이 사용자를 해당 SSO(Single Sign-On) 공급자 그룹에 자동으로 할당하고, 이에 따라 알맞은 Snowflake 역할과 Posit Connect 계정 설정이 프로비저닝됩니다.\u003C/p\u003E\r\n\u003Cp\u003E"Snowflake 생태계 안에 Posit을 배포하면 좋은 점은 Snowflake에서 구현한 제어 기능이 모든 액세스와 모든 사용자 역할, 그리고 사용자가 액세스할 수 있는 모든 테이블을 그대로 관리한다는 것입니다"라고 Mueller는 설명했습니다. "Posit Connect는 Snowflake의 권한 구조를 네이티브로 그대로 가져오기 때문에, IT 팀이 SSO 공급자를 통해 최상위 수준에서 권한을 관리할 수 있습니다"라고 언급하며, 이러한 거버넌스가 별도 설정 없이 바로 원활하게 작동한다고 덧붙였습니다.\u003C/p\u003E\r\n\u003Cp\u003E"이전 회사들에서는 Posit을 별도의 독립형 서버에 배포했기 때문에, Snowflake 내부의 네이티브 앱으로 옮긴 것은 아키텍처의 변화였습니다"라고 Mueller는 말했습니다. "하지만 원활한 거버넌스 덕분에 정말 강력한 시스템이 되었습니다. 이 방식으로 배포한 것을 단 1분도 후회한 적이 없고, 다시 하더라도 반드시 이렇게 할 것입니다."\u003C/p\u003E\r\n\u003Ch3\u003E정적인 PDF에서 인터랙티브 시나리오 플래닝으로 전환\u003C/h3\u003E\r\n\u003Cp\u003E이러한 전환 이전에도 Brilliant Earth에서 Mueller가 이끄는 데이터 사이언스 팀은 정교한 데이터 사이언스 모델을 활용해 투자 결정을 최적화해 왔습니다. 그 한 가지 예가 바로 이 회사의 독자적인 베이지안 마케팅 믹스 모델(MMM)입니다. Posit과 Snowflake를 결합하기 전에는 이러한 모델들을 데이터 사이언스 팀 자체만 주로 이용할 수 있었으며, 비즈니스 리더들에게는 요약 통계, PowerPoint 자료 및 기타 정적 권장 사항만이 제공되었습니다.\u003C/p\u003E\r\n\u003Cp\u003EMMM의 역량을 의사 결정권자가 직접 활용할 수 있도록, Mueller의 데이터 사이언스 팀은 Snowflake의 데이터를 모델의 기반으로 삼고 그 위에 Posit Connect에서 호스팅되는 인터랙티브 Streamlit 애플리케이션을 구축했습니다. 이제 Brilliant Earth의 성장 팀은 반응 곡선을 직접 탐색하고, 채널 성과를 평가하고, 예산을 설정하고, 채널 포화 지점 같은 제약 조건을 적용하며, 예상 매출과 ROI 지표까지 포함된 맞춤형 시나리오 시뮬레이션을 실행할 수 있습니다.\u003C/p\u003E\r\n\u003Cp\u003E"이 시나리오를 실제로 실행하는 데 필요한 최고의 도메인 전문 지식은 비즈니스 팀이 보유하고 있습니다"라고 Mueller는 언급했습니다. "이 프런트엔드 인터페이스를 구축해 의사 결정권자가 코드를 작성하지 않고도 데이터 모델과 직접 상호 작용할 수 있도록, 그 역량을 그들의 손에 직접 쥐여 주고자 합니다." Mueller에 따르면 성장 팀에 미친 영향은 지대했습니다.\u003C/p\u003E\r\n\u003Ch3\u003E100명 이상의 쇼룸 관리자를 위한 운영 현대화\u003C/h3\u003E\r\n\u003Cp\u003E다음 과제는 매장별 실적을 추적하는 100명 이상의 쇼룸 운영 사용자를 레거시 BI 플랫폼에서 새로운 환경으로 옮기는 일이었습니다. 이 전환으로 기존 소프트웨어 라이선스를 정리해 상당한 비용을 절감했지만, 사용자 도입을 이끄는 과정은 더 나은 사용자 경험을 만들 기회이기도 했습니다.\u003C/p\u003E\r\n\u003Cp\u003E"우리 모두는 습관의 동물"이라고 Mueller는 말했습니다. "궁극적으로는 누군가가 기존보다 개선되었다고 인식할 만한 것을 만드는 것이 중요합니다."\u003C/p\u003E\r\n\u003Cp\u003E분석 팀은 익숙한 정적 테이블을 단순히 재현하는 대신, 새로운 Posit 대시보드에 거버넌스가 적용된 대화형 인터페이스인 querychat을 결합했습니다. 이제 쇼룸 관리자는 복잡한 필터를 일일이 탐색하는 대신 "내 쇼룸의 지난 14일간 예약 실적을 보고 싶어"와 같은 자연어 프롬프트를 입력해 맞춤형 뷰를 즉시 확인할 수 있습니다.\u003C/p\u003E\r\n\u003Ch3\u003EAI를 통한 신뢰할 수 있는 서술형 보고서 생성\u003C/h3\u003E\r\n\u003Cp\u003E수학적 정확성을 희생하지 않으면서 수작업 주간 보고를 대체하기 위해, Brilliant Earth는 정량 계산과 텍스트 생성을 엄격하게 분리했습니다.\u003C/p\u003E\r\n\u003Cp\u003EPython 및 R 코드는 Snowflake 데이터에 대해 직접 필요한 지표를 계산합니다. 수치는 검증을 거친 뒤에야 LLM API로 전달되며, LLM은 이를 바탕으로 추세를 요약하고 주간 보고서를 자연어로 작성합니다.\u003C/p\u003E\r\n\u003Cp\u003E"LLM은 산문 형태의 요약에 사용하는데, 이 작업에는 정말 뛰어납니다. 하지만 계산은 수학 함수가 맡도록 하고 싶습니다. Posit Connect에 올리는 것은 코드 기반이라 검증할 수 있고, 반복 가능하며, 유지 관리가 쉽고, 신뢰할 수 있습니다"라고 Mueller는 말했습니다.\u003C/p\u003E\r\n\u003Ch3\u003E더 빨라진 프로토타이핑과 일회성 분석\u003C/h3\u003E\r\n\u003Cp\u003EAI 지원 코딩과 Snowflake 내에서 원활하게 실행되는 Posit 덕분에 맞춤형 애플리케이션 개발 속도가 매우 빨라졌습니다. 이제 팀은 즉각적이고 단기적인 요구 사항을 위해 설계된 경량 분석 도구를 구축할 여유가 생겼습니다.\u003C/p\u003E\r\n\u003Cp\u003E"Shiny 대시보드를 만들어 Posit에서 호스팅하고 Snowflake에 연결하는 과정이 이제 아주 빨라져서, 일회성 아티팩트를 만든다는 아이디어에 완전히 공감하게 되었습니다"라고 Mueller는 설명했습니다. "대부분의 경우 이런 아티팩트가 문제나 분석 내용을 훨씬 더 잘 설명하고, 이제는 몇 시간씩 들이지 않고도 빠르게 만들어 낼 수 있습니다."\u003C/p\u003E\r\n\u003Cp\u003EBrilliant Earth에서는 도메인 전문가들도 직접 솔루션의 프로토타입을 만들고 있습니다. Claude 같은 프런티어 모델을 거버넌스가 적용된 시맨틱 계층 위에 구축된 Snowflake CoWork 에이전트에 연결하면, 머천다이저는 캐럿 중량이나 판매 소진율 같은 특정 지표에 맞춘 맞춤형 보고서의 프로토타입을 만들 수 있습니다. 프로토타입이 여러 부서에 두루 유용하다고 입증되면, 분석 팀은 이를 검증된 Snowflake 데이터로 다시 구축해 엔터프라이즈급 애플리케이션으로 Posit Connect에 게시합니다.\u003C/p\u003E\r\n\u003Ch3\u003E엔터프라이즈 전반으로 거버넌스 확장\u003C/h3\u003E\r\n\u003Cp\u003EBrilliant Earth가 다음으로 머천다이징, 디지털, 재무 팀의 온보딩을 준비하는 가운데, 비즈니스 분석의 다음 단계를 구상하는 회사의 목표는 기존 방식의 복제가 아닌 재창조입니다. \u003C/p\u003E\r\n\u003Cp\u003E"계속 늘어나는 대시보드를 끝없이 다시 만들고 싶지는 않습니다"라고 Mueller는 말했습니다. "그보다는 사용자가 무엇을 원하는지 파악하고, 해당 이해관계자와 협력해 완전히 맞춤화된 솔루션을 만들고 싶습니다. 2년 후에도 쓰고 싶은 것을 만들고자 합니다."\u003C/p\u003E\r\n\u003Cp\u003E이 접근 방식은 현대 리테일 데이터 전략에 중요한 교훈을 보여 줍니다. Snowflake의 리테일 및 소비재 산업 리드인 Sem Sergunin은 정제되지 않은 원시 데이터에 AI 에이전트를 배포하면 "혼란만 키울 뿐"이라고 경고한 바 있습니다. Brilliant Earth는 Snowflake에 거버넌스가 적용된 데이터를 구축하고, 바로 그 데이터 옆에서 데이터 사이언티스트가 Posit의 강력한 환경을 활용하게 하며, 비즈니스 전문가에게는 인터랙티브 도구를 직접 제공함으로써 이 함정을 피했습니다.\u003C/p\u003E\r\n\u003Ch3\u003E전체 사례 읽기\u003C/h3\u003E\r\n\u003Cp\u003E온디맨드 웨비나 \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/en/webinars/customer-webinar/inside-brilliant-earths-ai-transformation-with-snowflake-posit-2026-10-07/?utm_source=snowflake&utm_medium=blog&utm_campaign=wbr-inside-brilliant-earth-ai-transformation&utm_content=cta-webinar\"\u003ESnowflake + Posit과 함께하는 Brilliant Earth의 AI 전환\u003C/a\u003E에서 \u003Ca target=\"_blank\" href=\"https://posit.co/solutions/snowflake?utm_source=partner&utm_medium=web&utm_term=snowflake&utm_content=brilliant-earth-custstory\"\u003ESnowflake 및 Posit\u003C/a\u003E을 활용한 Brilliant Earth의 데이터 전환 이야기를 Matthias Mueller와 Natallia Drobau에게서 직접 들어 보고, 마케팅 믹스 시나리오 플래너 데모도 확인해 보세요. 거버넌스가 적용된 맞춤형 분석 앱을 비즈니스 팀에 도입하려면 Snowflake Marketplace에서 \u003Ca target=\"_blank\" href=\"https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team-native-app\"\u003EPosit Team Native App\u003C/a\u003E을 살펴보세요. 30일 무료 Trial로 시작할 수 있습니다.\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnCount":12,"columnClassNames":{},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"layout":"RESPONSIVE_GRID","columnCount":12,"columnClassNames":{"author_chip":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","id":"container-959357496f",":type":"snowflake-site/components/container",":items":{"author_chip":{"id":"author-chip-fffc080ad9","title":{"id":"title","type":"heading2","lines":["Learn more about the authors"],":type":"snowflake-site/components/title-v2"},"authors":[{"authorImage":{"id":"image-089dc4bcf9","alt":"Untitled design - 1","height":"1349","lazyEnabled":true,"src":"/adobe/dynamicmedia/deliver/dm-aid--1d9773f9-daec-411d-8755-2ef702327fd5/amarrujofornacasq.png?quality=85&preferwebp=true","isLcpImage":false,"width":"1080",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-c0c3140898","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/angela-marrujo-fornaca/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Angela Marrujo Fornaca"},"authorTitle":"Senior Content Marketing Manager"},{"authorImage":{"id":"image-0871a85fa3","alt":"Matthias Mueller","height":"4032","lazyEnabled":true,"src":"/adobe/dynamicmedia/deliver/dm-aid--722f9b99-203c-4592-ab69-071648292d35/mm-original.jpg?quality=85&preferwebp=true","isLcpImage":false,"width":"3024",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-52087c2487","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/matthias-mueller/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Matthias Mueller"},"authorTitle":"Senior Director, Data Science and Analytics, Brilliant Earth"},{"authorImage":{"id":"image-cc03a687fa","alt":"Natallia 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