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SnowConvert AI 활용’에서 이렇게 설명했습니다. “데이터 전략이 없다면 AI 전략도 없습니다. 그 위에 무언가를 제대로 구축하려면 먼저 데이터를 정비해야 합니다.”\u003C/p\u003E\n\u003Cp\u003E성과를 내고 있는 정부 조직은 완벽한 예산 주기나 의무 지침을 기다리지 않습니다. 데이터 파운데이션을 미션 크리티컬 자산으로 보고, 그에 맞춰 조직을 발전시키고 있습니다. \u003C/p\u003E\n\u003Ch2\u003E멀트노마 카운티의 데이터 사일로 해소 방식\u003C/h2\u003E\n\u003Cp\u003E오리건주에서 가장 큰 카운티이자 포틀랜드가 속한 멀트노마 카운티는 10년 된 SQL Server 환경을 운영하고 있었습니다. 이 환경은 수십 개의 비즈니스 인텔리전스 워크로드에 걸쳐 있었고, 이미 오래전에 조직을 떠난 엔지니어들이 구축한 것이었습니다. 문서화가 미흡했습니다. 아키텍처는 일관성이 없었습니다. 비용은 계속 증가했습니다.\u003C/p\u003E\n\u003Cp\u003E카운티는 최신 데이터 플랫폼으로 마이그레이션해야 했습니다. 공공 부문 조직에서 흔히 그렇듯 수년씩 지연하지 않고 빠르게 마이그레이션하기를 원했고, 실제로 팀은 5개월 만에 마이그레이션을 완료했습니다.\u003Csup\u003E1\u003C/sup\u003E\u003C/p\u003E\n\u003Cp\u003E카운티는 Snowflake의 SnowConvert AI를 활용해 결정론적 코드 변환과 복잡한 작업에 대한 AI 지원 처리를 결합한 하이브리드 마이그레이션 접근 방식을 사용했습니다. 여기에는 수동 재작성 대신 동적 SQL, 코드 수정, 자동화된 테스트 케이스 생성이 포함되었습니다. 카운티는 마이그레이션 일정 단축, 향후 레거시 SQL Server 라이선스 비용 지출 감소, 표준화된 아키텍처 구축이라는 성과를 보고했습니다. 이 아키텍처에는 보건 및 복지 서비스, 공공 안전, 미국 최대 규모의 도서관 시스템 중 하나 등 이전에는 사일로화되어 있던 여러 사업 부문이 포함되었습니다.\u003C/p\u003E\n\u003Cp\u003E멀트노마 카운티의 선임 데이터베이스 관리자 Michael Hanna는 마이그레이션 성공 요인을 명확히 짚었습니다. “데이터를 준비하고 마이그레이션을 준비하는 데 들인 시간은 결국 몇 배의 효과로 돌아옵니다.”\u003C/p\u003E\n\u003Ch3\u003E레거시 도구를 계속 사용하는 조직을 위한 멀트노마의 3가지 교훈\u003C/h3\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E예상보다 더 일찍 시작하기: \u003C/b\u003E멀트노마는 갱신 계약 기한 중 하나를 3개월 앞두고 마이그레이션을 시작했지만, 결국 충분한 준비 기간을 확보하지 못했습니다. 멀트노마 팀은 가급적 라이선스 기한보다 1년 이상 앞서 마이그레이션 작업을 시작할 것을 권장합니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E모든 것을 마이그레이션하지는 않기: \u003C/b\u003E유지할 것, 아카이브할 것, 폐기할 것을 파악해야 합니다. 워크로드를 적정 규모로 조정하면 새로운 환경이 간소화되고 프로젝트의 전체 비용도 줄어듭니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E테스트에 충분한 시간 배정하기: \u003C/b\u003E코드 변환에는 몇 주가 걸릴 수 있습니다. 검증과 병렬 환경 테스트에는 몇 달이 걸립니다. 이에 맞춰 계획을 세워야 합니다.\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch2\u003E샌프란시스코가 도시 전반의 데이터 문화를 구축하는 방식\u003C/h2\u003E\n\u003Cp\u003E샌프란시스코시 및 카운티의 최고 데이터 책임자(CDO) Soumya Kalra와 팀은 최신화 여정의 비교적 초기 단계에 있습니다. Kalra가 직면한 가장 시급한 과제는 정부 조직에서 흔히 나타나는 문제입니다. 그동안 각 부서는 저마다의 시스템과 자체 개발 데이터베이스, ‘좋은 데이터’에 대한 각자의 정의를 갖춘 채 독립적으로 운영되어 왔습니다.\u003C/p\u003E\n\u003Cp\u003EKalra 팀이 집중하는 것은 기술 스택 업데이트만이 아닙니다. 데이터 인사이트가 서비스 제공 방식에 실질적으로 자리 잡도록 문화를 전환하는 데에도 힘쓰고 있습니다.\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"},"quote_item":{"id":"quote-item-be51a78626","alignment":"left","layout":"card","quoteSourceName":"Soumya Kalra","quoteSourceTitle":"Chief Data Officer, City and County of San Francisco","showQuoteIcon":false,"quote":"“서비스 제공 과정 곳곳에 데이터가 자리 잡은 모습을 꼭 만들고 싶습니다. 그러려면 그 과정에서 어떤 데이터를 수집해야 부서별 리더들이 프로세스를 계속 다듬어 갈 수 있을지 고민해야 합니다.”","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"blog_text_877633460":{"id":"blog-text-83573c4b58","text":"\u003Cp\u003E \u003C/p\u003E\n\u003Cp\u003E목표는 부서별 사일로를 해소하는 도시 전반의 통합 데이터 플랫폼입니다. 지금까지 이러한 사일로는 기관 간 인사이트를 구조적으로 불가능하게 만들었습니다. 하지만 Kalra는 먼저 무엇이 필요한지 분명히 알고 있습니다. 도시 전반에서 데이터를 통합하기 전에, 팀은 사람들이 참여하고 싶어지도록 신뢰와 공통 표준을 쌓고 내부 챔피언을 확보해야 합니다.\u003C/p\u003E\n\u003Cp\u003E이는 IT 부서뿐 아니라 운영 전반의 이해관계자를 처음부터 참여시켜야 한다는 의미입니다. 예를 들어 파이프라인을 구축한 엔지니어뿐 아니라, 질문에 답해야 하는 공중보건 부서의 분석가를 기준으로 설계해야 합니다. 또한 최신화가 지속될지 여부를 결정하는 것은 기술이 아니라 변화 관리라는 점을 받아들여야 합니다. \u003C/p\u003E\n\u003Cp\u003E샌프란시스코시 및 카운티의 사례는 마이그레이션 일정과 기술적 벤치마크가 주를 이루는 최신화 논의에 유용한 균형을 더해 줍니다. 때로 가장 중요한 작업은 코드 변환이 아닙니다. 노력을 들여 다른 방식으로 일할 가치가 있다고 조직을 설득하는 일입니다.\u003C/p\u003E\n\u003Ch2\u003E기술 부채에서 AI 도약의 발판으로\u003C/h2\u003E\n\u003Cp\u003E최신화에 성공한 공공 부문 조직에는 공통된 관점 전환이 있습니다. 마이그레이션을 일회성 프로젝트로 보지 않고, 데이터를 전략적 자산으로 관리하는 방식의 전환으로 바라봅니다.\u003C/p\u003E\n\u003Cp\u003E즉, 오늘 결정한 아키텍처를 3~5년 뒤에 다시 구축할 필요가 없어야 합니다. 이는 통합되고 거버넌스가 적용된 데이터 파운데이션이 최종 목표가 아니라는 인식을 의미합니다. 데이터 파운데이션은 기관 간 인사이트, 예측 분석, 그리고 이전에는 불가능했던 AI 기반 서비스 제공 등 앞으로 이어질 모든 것을 위한 발판입니다.\u003C/p\u003E\n\u003Cp\u003E앞으로 나아갈 길은 명확한 순서를 따릅니다.\u003C/p\u003E\n\u003Col\u003E\n\u003Cli\u003E\u003Cp\u003E파운데이션 최신화 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E데이터 자산 환경 통합 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003EAI 워크로드 활성화\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ol\u003E\n\u003Ch2\u003E성과를 내는 조직의 공통된 특징\u003C/h2\u003E\n\u003Cp\u003E앞서 나가는 조직은 데이터 파운데이션을 더 이상 백오피스의 관심사로 보지 않고, 미션 우선순위로 다루기 시작했습니다.\u003C/p\u003E\n\u003Cp\u003EAI 지원 마이그레이션, 자동화된 테스트, 거버넌스가 적용된 데이터 플랫폼처럼 이 여정을 가속화할 도구는 이미 모두 존재합니다. 관건은 기관들이 이를 활용할 준비 기간과 선견지명을 갖추고 있느냐입니다.\u003C/p\u003E\n\u003Cp\u003E안전하게 협업하고 데이터를 실행 가능한 인사이트로 전환하며, 클라우드 효율성으로 리소스를 극대화하고, AI를 위한 신뢰할 수 있는 데이터 파운데이션으로 혁신을 가속화하는 방법을 \u003Ca target=\"_blank\" href=\"https://www.snowflake.com/ko/solutions/industries/public-sector/\"\u003E자세히 알아보세요\u003C/a\u003E.\u003C/p\u003E\n\u003Cp\u003E \u003C/p\u003E\n\u003Cp\u003E\u003Csup\u003E1 \u003C/sup\u003E\u003Csub\u003ESnowflake Summit 세션 MI201: ‘AI 기반 최신화: 미 오리건주 멀트노마 카운티의 SnowConvert AI 활용’\u003C/sub\u003E\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text","quote_item","blog_text_877633460"],":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-6d723cc258",":type":"snowflake-site/components/container",":items":{"author_chip":{"id":"author-chip-1c69b41811","title":{"id":"title","type":"heading2","lines":["Learn more about the 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All Rights Reserved ㅣ 스노우플레이크코리아 유한회사 ㅣ 대표자: 마이클파스콸스카펠리 ㅣ 주소: 서울특별시 강남구 테헤란로 134, 10층(역삼동, 포스코타워 역삼) ㅣ 사업자등록번호: 523-87-02399\u003C/li\u003E\r\n\u003C/ul\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-small text-color-text-04"},"markup_editor":{"id":"markup-editor-622018edbe","title":" ","htmlContent":"\u003Cdiv class=\"sf-footer__social\"\u003E\r\n\u003Cdiv data-testid=\"snowflake-footer-twitter\" class=\"snowflake-button-icon snowflake-button-white snowflake-footer-social-item\"\u003E\u003Cdiv class=\"snowflake-button-icon \"\u003E\u003Ca href=\"https://x.com/Snowflake\" data-testid=\"button-external\" aria-label=\"X (Twitter)\" role=\"button\" class=\"snowflake-button-container\" title=\"X (Twitter)\" tabindex=\"0\" target=\"_blank\" rel=\"noreferrer\"\u003E\u003Cdiv data-testid=\"button-icon-wrapper\"\u003E\u003Csvg xmlns=\"http://www.w3.org/2000/svg\" fill=\"none\" viewBox=\"0 0 59 53\" class=\"button-icon\"\u003E\u003Cpath 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