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Earthがチャネル全体で拡大するにつれて、インサイトに対する欲求は、従来のレポートが提供できるよりも早く成長しました。慎重に構築された週次のデータサイエンスレポートは特定の時点を捉えていましたが、チームは提供スピードに機会を見出しました。会社全体の意思決定者が、同じ信頼できるデータに直接、セルフサービスでアクセスできたらどうなるかについて解説します。\u003C/p\u003E\n\u003Cp\u003EPositのSenior Solutions AdvisorであるNatallia Drobau氏は、「Brilliant Earthにはすでに非常に有能なデータサイエンスチームと、適切にガバナンスが効いたデータがありました」と述べています。「機会は、そのチームのリーチを拡大し、彼らのモデルとインサイトが単一のレポートチャネルを通じて流れるのではなく、ビジネス全体の意思決定を促進できるようにすることでした。」\u003C/p\u003E\n\u003Cp\u003EBrilliant EarthのAnalytics and Data Science担当Senior DirectorであるMatthias Mueller氏は、その社内の人材こそが、会社のアプローチを変えるまさにその理由であると考えました。「Brilliant Earthには素晴らしい人材がいます。私がこれまで一緒に働いた中で最高の人たちの何人かがここで働いています」とMueller氏は述べています。「それはまさに、そのすべての才能を活用するために、人々を同じガバナンスが効いたエコシステムと同じプラットフォームに導こうとする取り組みでした。」\u003C/p\u003E\n\u003Cp\u003Eデータサイエンスとリアルタイムの実行の間のギャップを埋めるために、Brilliant EarthはSnowflakeとPositに目を向けました。Positは、RStudio、Shiny、Quartoなどの広く使用されているオープンソースのデータサイエンスツールや、PythonとRでデータサイエンスの作業を構築、公開、共有するためのエンタープライズプラットフォームであるPosit Teamを提供するソフトウェア企業です。Brilliant EarthがSnowflake内でPositをネイティブに展開し、中央のアナリティクス機能をトランザクション型のレポートデスクからセルフサービスデータ製品の戦略的ビルダーへとどのように変革したかを探ります。\u003C/p\u003E\n\u003Ch3\u003Eインフラストラクチャレベルでのガバナンスのボトルネックの解消\u003C/h3\u003E\n\u003Cp\u003E多くの小売企業では、チームが独自の孤立したツールを採用するため、データの民主化が行き詰まり、結果としてレポートの競合やIT部門にとっての管理上の悪夢が生じます。\u003C/p\u003E\n\u003Cp\u003EBrilliant Earthは、Snowparkコンテナサービス上で実行されるSnowflake Native AppとしてPosit Teamをインストールすることで、このガバナンスのジレンマを解決しました。メンテナンスと監視を必要とする冗長なセキュリティプロトコルを備えた個別のサーバーを維持する代わりに、同社はPositをSnowflake環境に直接統合しました。\u003C/p\u003E\n\u003Cp\u003Eユーザーのプロビジョニングは現在、完全に自動化されています。従業員は、ITチケットシステムのタイルをクリックしてPositへのアクセスをリクエストします。リクエスターのマネージャーとアナリティクスチームがそれを承認すると、システムは自動的にユーザーを正しいシングルサインオン（SSO）プロバイダーのグループに割り当て、これにより正しいSnowflakeロールとPosit Connectアカウント設定のプロビジョニングがトリガーされます。\u003C/p\u003E\n\u003Cp\u003E「Snowflakeのエコシステム内にPositを展開することの素晴らしい点は、Snowflakeで実装する制御が、すべてのアクセス、すべてのユーザーロール、誰かがアクセスできるすべてのテーブルを引き続き管理することです」とMueller氏は説明しました。「Posit ConnectはSnowflakeから許可の構造をネイティブに推論するため、ITチームはSSOプロバイダーを介して管理されるトップレベルで許可を担当できます」と彼は指摘し、このガバナンスはすぐにシームレスに機能すると付け加えました。\u003C/p\u003E\n\u003Cp\u003E「以前の会社でPositを個別のスタンドアロンサーバーに展開したことがあるため、Snowflake内のネイティブアプリへの移行はアーキテクチャの転換でした」とMueller氏は指摘しました。「しかし、シームレスなガバナンスにより、信じられないほど強力なシステムになります。このように展開したことを一瞬たりとも後悔していませんし、間違いなくもう一度このようにするでしょう。」\u003C/p\u003E\n\u003Ch3\u003E静的なPDFからインタラクティブなシナリオプランニングへの移行\u003C/h3\u003E\n\u003Cp\u003E変革の前でさえ、Brilliant EarthのMueller氏のデータサイエンスチームは、投資の選択を最適化するために洗練されたデータサイエンスモデルを使用していました。そのような例の1つが、同社独自のベイジアンマーケティングミックスモデル（MMM）です。PositとSnowflakeを組み合わせる前は、これらのモデルにアクセスできるのは主にデータサイエンスチーム自身であり、ビジネスリーダーには要約統計、PowerPointの資料、その他の静的な推奨事項が提供されていました。\u003C/p\u003E\n\u003Cp\u003EMMMの力を意思決定者の手に直接委ねるために、Mueller氏のデータサイエンスチームはSnowflakeからのデータにモデルの基礎を置き、その上にPosit ConnectでホストされるインタラクティブなStreamlitアプリケーションを構築しました。今日、Brilliant Earthの成長チームは、応答曲線を独自に調査し、チャネルのパフォーマンスを評価し、予算を設定し、チャネルの飽和点などの制約を適用し、予測される収益とROIメトリクスを備えたカスタムシナリオシミュレーションを実行できます。\u003C/p\u003E\n\u003Cp\u003E「これらのシナリオを実際に実行するために必要な最高のドメイン専門知識は、当社のビジネスチームにあります」とMueller氏は指摘しました。「このフロントエンドインターフェイスを構築することで、意思決定者の手に直接力を委ね、コードを書くことなくデータモデルと対話できるようにすることを目指しています。」Mueller氏によると、成長チームへの影響は甚大です。\u003C/p\u003E\n\u003Ch3\u003E100人以上のショールームマネージャーのオペレーションのモダナイズ\u003C/h3\u003E\n\u003Cp\u003E次の大きなテストは、店舗レベルのパフォーマンスの追跡を担当する100人以上のショールームオペレーションユーザーを、レガシーBIプラットフォームから移行させることでした。この移行により、古いソフトウェアライセンスを削減することで大幅なコスト削減が実現しましたが、導入の推進は、優れたユーザー体験を生み出す機会でもありました。\u003C/p\u003E\n\u003Cp\u003E「私たちは皆、習慣の生き物です」とMueller氏は述べています。「最終的には、誰かが今持っているものよりも改善されていると感じるものを構築することです。」\u003C/p\u003E\n\u003Cp\u003Eアナリティクスチームは、使い慣れた静的なテーブルを単に再作成するのではなく、新しいPositダッシュボードを、ガバナンスが効いた対話型インターフェイスであるquerychatでラップしました。ショールームマネージャーは、複雑なフィルターを操作する代わりに、「私のショールームの過去14日間の予約パフォーマンスを探しています」などの自然言語のプロンプトを送信し、カスタマイズされたビューを即座に取得できるようになりました。\u003C/p\u003E\n\u003Ch3\u003EAIを使用した信頼できるナラティブレポートの生成\u003C/h3\u003E\n\u003Cp\u003E数学的な正確さを犠牲にすることなく手動の週次レポートを置き換えるために、Brilliant Earthは定量的な計算とテキスト生成の間に厳格な分離を確立しました。\u003C/p\u003E\n\u003Cp\u003EPythonとRのコードは、Snowflakeデータに対して直接必要なメトリクスをコンピュートします。数値が検証された後にのみ、それらはLLMのAPIに渡され、トレンドを要約し、自然言語で週次レポートを作成します。\u003C/p\u003E\n\u003Cp\u003E「私たちは散文で要約するためにLLMを使用しており、それは本当に優れています。しかし、私は数学関数に計算を所有させたいのです。私たちがPosit Connectに置くものはコードベースであり、それは検証可能であることを意味します。それは再現可能で、保守可能で、信頼性があります」とMueller氏は述べています。\u003C/p\u003E\n\u003Ch3\u003E迅速なプロトタイピングと使い捨てアナリティクスの加速\u003C/h3\u003E\n\u003Cp\u003EAI支援コーディングとSnowflake内でシームレスに実行されるPositにより、カスタムアプリケーションの開発は信じられないほど速くなりました。チームは現在、即時の短期的なニーズに合わせて設計された軽量の分析ツールを構築する余裕があります。\u003C/p\u003E\n\u003Cp\u003E「Shinyダッシュボードを持ち、それをPositでホストし、Snowflakeに接続することが今では非常に迅速になったため、使い捨てのアーティファクトを生成するというアイデアに本当に賛同しています」とMueller氏は説明しました。「ほとんどの場合、それらは問題や分析をはるかにうまく説明しており、構築に何時間も費やすことなくそれらを生み出すことが可能になりました。」\u003C/p\u003E\n\u003Cp\u003EBrilliant Earthでは、ドメインの専門家も独自のソリューションのプロトタイピングを積極的に行っています。Claudeなどのフロンティアモデルを、ガバナンスが効いたセマンティックレイヤー上に構築されたSnowflake CoWorkエージェントに接続することで、マーチャンダイザーは、カラット重量やセルスルー率などの特定のメトリクスに合わせたカスタムレポートのプロトタイプを作成できます。プロトタイプが広く価値があることが証明された場合、アナリティクスチームは検証済みのSnowflakeデータ上でそれを再構築し、エンタープライズグレードのアプリケーションとしてPosit Connectに公開します。\u003C/p\u003E\n\u003Ch3\u003E企業全体でのガバナンスの拡張\u003C/h3\u003E\n\u003Cp\u003EBrilliant Earthが次にマーチャンダイジング、デジタル、財務チームをオンボーディングしようとしているため、同社がビジネスアナリティクスの次のフェーズへの移行を想像する際の目標は、レプリケーションではなく再発明です。 \u003C/p\u003E\n\u003Cp\u003E「増え続けるダッシュボードを再構築したくありません」とMueller氏は述べています。「私はただ、誰かが何を望んでいるのかを把握し、そのステークホルダーと協力して、代わりにそれらを完全にカスタムのソリューションとして構築したいだけです。私たちは、2年後にも使いたいと思うものを構築しようとしています。」\u003C/p\u003E\n\u003Cp\u003Eこのアプローチは、モダンな小売データ戦略にとって重要な教訓を反映しています。Snowflakeの小売・消費財担当Industry LeadであるSem Sergunin氏が警告したように、準備されていない生のデータにAIエージェントを展開することは、「混乱を拡大する」ことにしかなりません。Brilliant Earthは、Snowflakeにガバナンスが効いたデータを確立し、データサイエンティストにそのデータのすぐ隣にあるPositの堅牢な環境を提供し、インタラクティブなツールをビジネスの専門家の手に直接委ねることで、この罠を回避しました。\u003C/p\u003E\n\u003Ch3\u003E詳細を見る\u003C/h3\u003E\n\u003Cp\u003Eオンデマンドウェビナー「\u003Ca 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\" target=\"_blank\"\u003EInside Brilliant Earth's AI Transformation With Snowflake + Posit\u003C/a\u003E」を視聴して、Matthias Mueller氏とNatallia Drobau氏から\u003Ca href=\"https://posit.co/solutions/snowflake?utm_source=partner&utm_medium=web&utm_term=snowflake&utm_content=brilliant-earth-custstory\" target=\"_blank\"\u003ESnowflakeとPosit\u003C/a\u003Eを使用したBrilliant Earthのデータ変革について詳しく聞き、マーケティングミックスシナリオプランナーのデモをご覧ください。カスタムでガバナンスが効いたアナリティクスアプリを自社のビジネスチームに提供するには、Snowflakeマーケットプレイスで\u003Ca href=\"https://app.snowflake.com/marketplace/listing/GZTSZMCB9S/posit-pbc-posit-team-native-app\" target=\"_blank\"\u003EPosit Team Native App\u003C/a\u003Eを探索してください。ここでは、30日間の無料トライアルを開始できます。\u003C/p\u003E\n","richText":true,":type":"snowflake-site/components/blog/blog-text"}},":itemsOrder":["blog_text"],":type":"wcm/foundation/components/responsivegrid"},"responsivegrid_premium_content_banner":{"columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{},"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"layout":"RESPONSIVE_GRID","columnCount":12,"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"author_chip":"aem-GridColumn aem-GridColumn--default--12"},"id":"container-166c04bfc4",":type":"snowflake-site/components/container",":items":{"author_chip":{"id":"author-chip-7cf92d0398","title":{"id":"title","type":"heading2","lines":["Learn more about the 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Mueller","lazyEnabled":true,"isLcpImage":false,"width":"3024",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-57e5c2d3d6","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/matthias-mueller/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Matthias Mueller"},"authorTitle":"Senior Director, Data Science and Analytics, Brilliant Earth"},{"authorImage":{"id":"image-9e33dd7763","height":"2275","src":"/adobe/dynamicmedia/deliver/dm-aid--b24bdf71-47d7-443c-8460-829308aaf979/natallia-drobau-%25281%2529.jpg?preferwebp=true&quality=85","alt":"Natallia Drobau","lazyEnabled":true,"isLcpImage":false,"width":"1819",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-35ca7b9696","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/natallia-drobau/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Natallia Drobau"},"authorTitle":"Senior Solutions Advisor, Posit"},{"authorImage":{"id":"image-0e3a14489a","height":"512","src":"/adobe/dynamicmedia/deliver/dm-aid--308d8981-6213-4584-8c66-3a4241ae1824/sem-sergunin.png?preferwebp=true&quality=85","lazyEnabled":true,"isLcpImage":false,"width":"512",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-8488c6baa4","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/sem-sergunin/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Sem Sergunin"},"authorTitle":"Global 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