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Intelligenceを業界対応のエージェントにパッケージ化し、ダッシュボードの枠を超えて、チームが自然言語でより的確な質問を行えるよう支援している様子を紹介します。\u003C/p\u003E\r\n\u003Ch3\u003EAnblicks：売上、マージン、プロモーションのアトリビューションを自動化する小売業界のエグゼクティブ向けインテリジェンス\u003C/h3\u003E\r\n\u003Cp\u003EAnblicksは、Snowflake Intelligence上にL2推論レイヤーを構築し、「何が起きたか」というレポートの枠を超え、「なぜ起きたか」「次に何をすべきか」について、エグゼクティブ向けの一貫した回答を提供しています。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E1つのナラティブ：\u003C/b\u003Eアナリストが複数のダッシュボードやデータセットを手作業でつなぎ合わせる代わりに、リーダーは日々の業績について自然言語で質問し、売上、マージン、プロモーション、在庫可用性、店舗/バナーの業績を結び付けた、根拠のあるナラティブを受け取ることができます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E全体像：\u003C/b\u003Eこのソリューションは、複数の小売シグナルを横断して推論し、エグゼクティブサマリーを作成します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ECitiusTech：医療従事者向けのヘルスケアインサイトエージェント\u003C/h3\u003E\r\n\u003Cp\u003ECitiusTechのHealthcare Insights Agentは、Snowflakeネイティブのモジュール式対話型アナリティクスソリューションであり、セマンティックレイヤーを通じて構造化データと非構造化データを統合し、リアルタイムのインサイトを提供します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E統合されたガバナンス：\u003C/b\u003EこのエージェントはHIPAAコンプライアンスをサポートし、セキュアで、CitiusTechのQuality and Trustフレームワークと統合されています。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eインサイトの迅速化：\u003C/b\u003Eこのエージェントにより、ITチームやBIダッシュボードへの依存が軽減され、重要なインサイトを得るまでの時間が短縮されます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E自然な統合：\u003C/b\u003E医療チームや医療従事者が自然言語で質問すると、推奨されるアクションや実用的なインサイトがヘルスケアワークフローに組み込まれた形で提供されます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ECognizant：Snowflake Intelligenceが支援するヘルスケアプランショッパー\u003C/h3\u003E\r\n\u003Cp\u003ECognizantは、その深い業界専門知識を活用し、Snowflake Intelligenceと連携して、複雑なヘルスケアプランの選択をナビゲートするパーソナライズされたアプローチを構築しました。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E幅広い視点：\u003C/b\u003Eこのソリューションは、メンバーの好み、臨床プロファイル、さまざまな支払者ソース、給付金に関するドキュメント、プラン固有の処方集ドキュメント、プロバイダーディレクトリなど、大量のヘルスケアデータを処理します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E個別の成果：\u003C/b\u003Eヘルスケアプランショッパーは、各加入者にパーソナライズされた推奨事項を生成し、カスタマイズされた無駄のないシームレスなエクスペリエンスを生み出します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EDeloitte：金融サービス向けエンタープライズ顧客アナリティクスプラットフォームのモダナイゼーション\u003C/h3\u003E\r\n\u003Cp\u003EDeloitteは、レガシーなOracleデータウェアハウスをSnowflakeに移行することで、米国トップクラスの金融機関向けにAIファーストの顧客アナリティクスプラットフォームを構築しました。これには、プラットフォームの立ち上げ（セキュリティ、DevOps、コントロールプレーン）、データエンジニアリング、セマンティックレイヤー、AIイネーブルメントが含まれます。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E大規模な移行：\u003C/b\u003EDeloitteは、DeloitteのData AssistインジェスチョンアクセラレーターとAWS上のSnowflakeイベントベースのインジェスチョンを使用して、100以上のテーブルにまたがる数十億件のレコードを移行し、顧客アナリティクス、セグメンテーション、階層管理、製品アトリビューションをサポートしています。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E持続的なインサイト：\u003C/b\u003Eこのアプローチでは、ビジネスロジックをBIツールから、再利用可能でガバナンスの効いたSnowflakeデータプロダクトへとレフトシフトし、セマンティックビューやインターナルマーケットプレイスを通じて公開します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E多面的なソリューション：\u003C/b\u003E3つの本番環境用Snowflake Intelligenceエージェント（Snowflake Cortex AnalystまたはSnowflake Cortex Search）が、顧客獲得、プロダクトの浸透、収益の最適化に向けたインサイトを提供します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch2\u003E部門のニーズをサポートするインテリジェンス\u003C/h2\u003E\r\n\u003Cp\u003ESnowflake Intelligenceの成功事例のすべてが、業界プラットフォームから始まっているわけではありません。多くのチームは、マーケティングパフォーマンス、収益インテリジェンス、コンタクトセンターアナリティクス、あるいは「生成AIをどこから始めるべきか」といった、特定の部門のワークフローから着手しています。以下のソリューションは、Snowflake Intelligenceが特定のチームや機能において、実践的な意思決定サポートをどのように強化できるかを示しています。\u003C/p\u003E\r\n\u003Ch3\u003EArchetype：PRISM\u003C/h3\u003E\r\n\u003Cp\u003EPRISMは、断片的な市場シグナルを意思決定レベルのインテリジェンスに変換します。これにより、組織はより迅速に行動し、リソースをより賢く割り当て、競争力に自信を持つことができるようになります。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E外部インサイト：\u003C/b\u003EPRISMは、ニュースの要約や一般的なトレンドの提示にとどまりません。テクノロジー、規制、競合他社、顧客の行動に関する外部シグナルを、組織の戦略とコンテキストというレンズを通して継続的に統合し、現在と今後において真に重要な事項を浮き彫りにします。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E信頼性と監査可能性：\u003C/b\u003ESnowflake上にネイティブに構築されたPRISMは、セキュアでガバナンスの効いた環境で稼働します。この環境では、インサイトは説明可能かつ監査可能であり、実際のビジネス成果と連携しています。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E時間との勝負に勝つ能力：\u003C/b\u003EPRISMは、初期の市場シグナルを優先順位付けされたアクションに変換します。これにより、リーダーは収益機会をより早く特定し、適切なタイミングでの意思決定を通じて利益率を保護・拡大し、コストが膨らむ前にリスクを軽減できます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EBlueCloud：Marketing Intelligence Agent\u003C/h3\u003E\r\n\u003Cp\u003EBlueCloudのMarketing Intelligence Agentは、Snowflake Intelligence上に構築され、本番環境にデプロイされたソリューションです。マーケティングパフォーマンスの分析と意思決定サポートを自動化します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003Eオンデマンドのインテリジェンス：\u003C/b\u003Eこのエージェントは、Cortex Analystと、ドメイン固有のビジネスロジックをエンコードしたカスタムセマンティックモデルを活用し、複雑な分析クエリをオンデマンドで生成します。これにより、週次のパフォーマンスレポートや前期間との比較を提供し、無駄な広告費やコンバージョン率の低下など、早急な対応が必要なキャンペーンを自動的にフラグ付けします。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eより豊富なコンテキスト：\u003C/b\u003Eこのエージェントは、ファーストパーティのマーケティングデータを、Snowflakeマーケットプレイスのサードパーティデータセット（競合ベンチマーク、オーディエンスの属性、業界トレンドデータなど）で強化します。これにより、パフォーマンス変動の背景にあるより深いコンテキストを提供します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E数時間から数秒へ：\u003C/b\u003Eすでにエンタープライズの顧客で稼働しているこのソリューションは、手作業による数時間のクエリ開発やダッシュボードの探索を、AIドリブンなインサイトにより数秒で完了させます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EHexaware：マーケティング向けAudience Match AI\u003C/h3\u003E\r\n\u003Cp\u003EAudience Match AI（AMAI）は、Snowflakeネイティブなマーケティングインテリジェンスアクセラレーターであり、顧客セグメンテーションとキャンペーン分析を合理化するように設計されています。このソリューションは、構造化された顧客データ（CSV/テーブル）をSnowflakeに取り込み、機械学習ベースのクラスタリングを適用して、明確な顧客ペルソナを生成します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E顧客の360度インサイト：\u003C/b\u003EStreamlitインターフェイスを通じて、顧客の360度ビュー、セグメントレベルのアナリティクス、インタラクティブな可視化を提供します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E対話型アナリティクス：\u003C/b\u003EAMAIはCortex Agentsを活用して、インテリジェントな対話型アシスタントを提供します。これにより、ユーザーは自然言語を使用して、クラスタリングされた顧客データや参照ドキュメントにクエリを実行できます。これは、Snowflake IntelligenceおよびSnowflake Cortex AIの機能によって強化されています。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EphData：Persona-Driven Revenue Intelligence Agent on Snowflake\u003C/h3\u003E\r\n\u003Cp\u003ESnowflake Intelligence上に構築されたphDataのPersona-Driven Revenue Intelligence Agentは、エグゼクティブや収益リーダーに対し、複雑なARR（年間経常収益）に関する質問への信頼できる回答を、シンプルな自然言語を用いて即座に提供します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E主要なメトリクス：\u003C/b\u003Eリーダーは、カスタムのアナリストレポートを何日も待つ代わりに、チャーンリスク、アップセルの可能性、更新時のエクスポージャーなどのシナリオを数秒で探索できます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eマルチステップ推論：\u003C/b\u003Eこのエージェントは、Snowflakeデータ全体にわたるマルチステップ推論を使用します。これにより、静的なダッシュボードだけでなく、トレンド、推進要因、リスクを浮き彫りにします。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eペルソナのマッチング：\u003C/b\u003E役割に基づく複数のペルソナ（エグゼクティブ、RevOps、財務など）を備えており、各ステークホルダーに適切なビジネスロジック、KPI、ビューを自動的に適用します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E手作業の削減：\u003C/b\u003E収益リーダーは、シンプルで直感的なUIの中で、手作業による分析の労力を削減できます。さらに、価格設定や更新に関する意思決定をより迅速かつ自信を持って行い、新たなARR成長の機会を発見することが可能です。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003ESlalom：Use Case Explorer\u003C/h3\u003E\r\n\u003Cp\u003E組織は生成AIの方向性に悩んでおり、「どこから始めるべきか」「ROIはどのくらいか」といった疑問を抱えています。チームは、自社の業界に関連する価値の高いユースケースを、市場主導で迅速に特定する必要があります。Use Case Explorerは、Snowflake Intelligence上に構築されたAI駆動のエージェントです。Slalomの業界専門知識とライブWeb検索を組み合わせることで、あらゆる業界のユースケースを提示、スコアリング、詳細化します。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003Eデータとトレンド：\u003C/b\u003EクライアントのデータやSIの経験は、新興市場のトレンドによって強化され、現在および将来の課題に対処します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eスマートなスタート：\u003C/b\u003E各ユースケースには、AIが計算した優先度スコア、推定ROI、実装の複雑さの評価が含まれており、どこから始めるべきかが明確になります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E意思決定の迅速化：\u003C/b\u003E調査やアイデア出しにかかる時間を数日から数分に短縮し、経営陣に明確な計画を提示します。これにより、「何ができるか」から「どのように実行するか」へと、議論を直ちに進めることができます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EVivanti：コールセンター向けConnect Analytics Accelerator\u003C/h3\u003E\r\n\u003Cp\u003EVivantiのConnect Analytics Acceleratorは、dbtとSnowflakeのAI駆動プラットフォームを使用して、AWS Connectのコンタクトセンターデータを戦略的なビジネスインテリジェンスに変換する、事前構築済みのアナリティクスソリューションです。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E数か月から数週間へ短縮：\u003C/b\u003Eこのアクセラレーターにより、組織は数か月ではなく数週間で、本番環境に対応したアナリティクスを実現できます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eビジネスユーザーと自然言語：\u003C/b\u003Eこのモデル上に構築されたセマンティックビューがSnowflake Intelligenceの機能を解放します。これにより、ビジネスユーザーは専門的な技術知識がなくても、通話、エージェントの活動、顧客とのやり取りについて、自然言語で質問できるようになります。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E俯瞰的な視点と詳細な分析：\u003C/b\u003E基盤となるスタースキーマ設計は、詳細な運用分析と経営層向けの戦略的レポートの両方をサポートし、連絡先、やり取り、キュー、エージェント、サービスライン全体にわたる包括的な可視性を提供します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eカスタマイズされた出力：\u003C/b\u003E組織はカスタムアナリティクスやレポートを迅速に構築できると同時に、ビジネスユーザーが対話型のAIドリブンなインサイトを通じて、コンタクトセンターのパフォーマンスを独自に調査できるようになります。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch2\u003E迅速な価値実現までの時間：数週間でSnowflake Intelligenceの運用を開始できるアクセラレーター\u003C/h2\u003E\r\n\u003Cp\u003E市場への投入スピードが最も重要な課題である場合、以下のアクセラレーターが役立ちます。これらは、チームがSnowflake Intelligenceの機能を立ち上げ、結果を検証し、強固な基盤を持って本番環境へ移行できるように設計された構造化エンゲージメントです。アクセラレーターは、事前構築済みの資産とSnowflake Intelligenceの機能を活用して、検証済みの本番環境に対応したユースケースを迅速に提供する、期限付きの構造化エンゲージメントです。\u003C/p\u003E\r\n\u003Ch3\u003E7Rivers：Conversational Analyticsアクセラレーター\u003C/h3\u003E\r\n\u003Cp\u003E7Riversは、すぐに使用でき、導入が容易で、拡張性を備えたビジネスファーストのAIソリューションにより、組織がSnowflake Intelligenceをより迅速に有効化できるよう支援します。Snowflake Cortex Analyst、Search、Agentの機能を活用することで、Conversational Analyticsアクセラレーターは、ビジネスユーザーが自然言語で質問できるようにします。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003ESQL不要のインタラクション：\u003C/b\u003Eユーザーは、SQLやアナリストに依存することなく、ガバナンスの効いたリアルタイムのインサイトを得ることができます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eプロトタイプから価値実現までの迅速化：\u003C/b\u003E7Riversは、実証済みのセマンティックモデリングパターン、AI対応ワークショップ、およびStreamlitベースの迅速なプロトタイプを組み合わせることで、測定可能な価値を迅速に提供します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E信頼できるデータ変換：\u003C/b\u003ECortex Agent APIを通じて既存のエンタープライズシステムにインテリジェンスを直接統合することで、7Riversは信頼できるデータを、ビジネス全体にわたる対話、インサイト、アクションへと変換します。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EDevoteam：Snowflake Intelligenceの価値実証（PoV）\u003C/h3\u003E\r\n\u003Cp\u003ESnowflake Intelligenceの価値実証（PoV）は、ガバナンスの効いたエージェント型データエクスペリエンスを通じて、測定可能なビジネスへの影響を実証するように設計された6週間のアクセラレーターです。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E構造化アプローチ：\u003C/b\u003E「計画と準備」「構築と展開」「測定と共有」という構造化された3段階の方法論により、優先度の高いビジネスドメインを調整し、最大15個の高価値の質問を定式化します。そして、それらの質問に大規模かつ確実に回答するために必要なセマンティックレイヤーとコネクタを実装します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E測定された成果：\u003C/b\u003E技術的なセットアップにとどまらず、Devoteamは変更管理、KPIトラッキング、経営層向けレポートを組み込み、導入率、生産性の向上、意思決定の迅速化を定量化します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eスケール能力：\u003C/b\u003Eその成果は、機能的なSnowflake Intelligenceプラットフォームだけでなく、ドメイン、地域、ユーザー層全体にソリューションを産業化し、拡張するための検証済みブループリントでもあります。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EKipi：Snowflake Intelligenceアクセラレーター\u003C/h3\u003E\r\n\u003Cp\u003EKipiのSnowflake Intelligenceアクセラレーターは、お客様がSnowflake Intelligenceの利用を開始できるようにする8週間の実装プログラムです。従来のBIツールから迅速に移行し、AIの力を活用して価値実現までの時間を短縮することで、競争上の優位性と運用効率を向上させます。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E意思決定の迅速化とインサイトのレイテンシー削減：\u003C/b\u003E信頼できるエンタープライズデータへの即時かつ対話型のアクセスをビジネスユーザーに提供し、アナリストや手作業によるレポートサイクルに依存することなく、リアルタイムの意思決定を可能にします。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003EAI投資から価値実現までの時間を短縮：\u003C/b\u003E本番環境に対応した対話型アナリティクスとAIアシスタントをより迅速に提供し、自動化されたインサイト、セルフサービスアナリティクス、運用工数の削減を通じて、測定可能なROIを実現します。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eエンタープライズへの導入とAIの拡張：\u003C/b\u003Eユーザーイネーブルメント、ガバナンスの調整、およびインテリジェントエージェントを部門横断で拡張する導入ロードマップを通じて、AIのインサイトを実際のビジネスワークフローに組み込みます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch3\u003EMerkle：Snowflake Intelligence評価フレームワーク\u003C/h3\u003E\r\n\u003Cp\u003E組織は、回答が正しいかどうかを知る体系的な方法を持たないまま、対話型アナリティクスを展開しています。そして、その確信がなければ、導入は行き詰まります。Merkleは、Snowflake Intelligenceのデプロイを評価するための専用アプリケーションを備えた、厳格な評価フレームワークを開発しました。このフレームワークは、Text-to-SQLの精度とエージェントの応答品質の両方をカバーしています。\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003E\u003Cb\u003E構造化された診断：\u003C/b\u003Eこのソリューションは、クライアントのセマンティックモデルに対して構造化されたテストスイートを実行します。そして、障害パターンを分類し、システムの問題箇所を正確に特定します。決定論的アプローチとLLM-as-judgeアプローチを組み合わせることで、各組織のユースケースに合わせたカスタム判定を柔軟に行うことができます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003Eお客様の環境に構築：\u003C/b\u003Eこの評価フレームワークは、すべてクライアントのSnowflake環境内で実行されます。データが境界外に出ることはなく、結果は完全な透明性を維持します。また、組織はシステムのパフォーマンスを証明するデータを完全に制御し続けることができます。\u003C/li\u003E\r\n\u003Cli\u003E\u003Cb\u003E信頼の蓄積：\u003C/b\u003E組織は、ベースラインを確立し、経時的な変化を検証するための評価インフラストラクチャを獲得できます。これにより、真の定着を促進する継続的な改善プロセスを構築できます。\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Ch2\u003ESnowflake Intelligenceのジャーニーを始める\u003C/h2\u003E\r\n\u003Cp\u003ESnowflake Intelligenceは、単一の部門、ワークフロー、または業界に限定されるものではありません。エンタープライズインテリジェンスエージェントとして、チームが断片化されたデータや時間のかかる分析から脱却し、深く説明可能なインサイトを得られるようにします。これにより、「何が起きているか」だけでなく「なぜ起きているか」にも答えることができます。ヘルスケアから金融サービス、マーケティングからコンタクトセンターに至るまで、そのパターンは一貫しています。エンタープライズデータへの信頼できる自然言語でのアクセスにより、より迅速で確信を持った意思決定が可能になります。\u003C/p\u003E\r\n\u003Cp\u003Eまた、組織が導入を開始するためのさまざまな方法も確認されています。専門家と提携して業界特化型エージェントをデプロイし、移行やモダナイゼーションの取り組みを加速させる組織もあれば、全社的なインテリジェンスプログラムを検証して拡張する組織もあります。一方で、Snowflake内で直接開始し、ビジネスユーザーが自ら、ガバナンスの効いた追跡可能な回答を得られるようにする組織もあります。\u003C/p\u003E\r\n\u003Cp\u003Eこれらのパートナーソリューションは、エコシステムの奥深さだけでなく、Snowflake Intelligence自体で実現できることの幅広さも示しています。\u003C/p\u003E\r\n\u003Cp\u003Eデータプラットフォームのモダナイゼーション、初の対話型アナリティクスエージェントの立ち上げ、またはオペレーショナルワークフローへのインテリジェンスの直接組み込みのいずれであっても、Snowflake Intelligenceは、組織のデータ活用方法を変革するための、セキュアでエンタープライズ対応の基盤を提供します。\u003C/p\u003E\r\n\u003Cp\u003Eエンタープライズインテリジェンスがビジネスにもたらす可能性をご確認ください。\u003C/p\u003E\r\n\u003Cp\u003ESnowflake Intelligenceが組織全体でセキュアなAIドリブンのデータワークフローをどのように強化するか、\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://www.snowflake.com/ja/product/snowflake-intelligence/?utm_source=[chatgpt.com](https://chatgpt.com)\"\u003E詳細をご確認ください\u003C/a\u003E。\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":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{},"columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{},":itemsOrder":[],":type":"wcm/foundation/components/responsivegrid"},"container_author_chip":{"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnClassNames":{"author_chip":"aem-GridColumn 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Child"}}],"publicationDate":"JUN 13, 2026","title":{"lines":["要求と設計：データエンジニアリングにおける2つの大きな転換への対応"],"type":"heading4",":type":"snowflake-site/components/title-v2"},"button":{"id":"button-ac4ff344c0","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/ja/blog/building-pipelines-for-ai/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"要求と設計：データエンジニアリングにおける2つの大きな転換への対応"},"image":{"id":"image-d5d1da0579","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--73ff60a0-5d78-44df-a242-8fba336496dc/44-general.jpg?preferwebp=true&quality=85","lazyEnabled":true,"height":"2160","width":"3840",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"tags":[{"tagText":"ストラテジーとインサイト","tagColor":"#29B5E8"}],"authors":[{"authorImage":{"id":"image-081221b75a","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--19dc31ed-b793-466f-bb8c-11c40115935f/amy-tu.png?preferwebp=true&quality=85","lazyEnabled":true,"height":"394","width":"422",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-a0f1cdb691","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/amy-tu-/"},"linkTargetContentType":"DOCUMENT_LEARN",":type":"snowflake-site/components/button","linkType":"SNOWFLAKE_INTERNAL","text":"Amy 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Intelligenceパートナーのソリューションが各業界のAI活用を加速させ、競争力を高める"},"image":{"id":"image-105ac2a522","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--df82ca42-ec45-41c3-8278-f444d9067892/11-snowflake.jpg?preferwebp=true&quality=85","lazyEnabled":true,"height":"720","width":"1680",":type":"snowflake-site/components/image"},":type":"snowflake-site/components/blog/card"},{"configurationStatus":{"configured":true,"message":""},"tags":[{"tagText":"ストラテジーとインサイト","tagColor":"#29B5E8"}],"authors":[{"authorImage":{"id":"image-f51ad5fa67","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--0136cbce-057c-4d36-b6ff-559ddff0ddb5/jennifer-b-author-image.jpg?preferwebp=true&quality=85","alt":"Jennifer 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href=\"https://www.snowflake.com/ja/legal/privacy/privacy-policy/#12\"\u003E個人情報を共有しない\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E\u003Ca href=\"https://www.snowflake.com/ja/legal/\"\u003E法務関連\u003C/a\u003E\u003C/li\u003E\r\n\u003Cli\u003E© 2026 Snowflake Inc. 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