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callout--general","text":"\u003Cp\u003E\u003Cstrong\u003E規制コンプライアンスの定義\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E規制コンプライアンスとは、データの収集、保護、活用、保管、廃棄に至るまで、組織のデータ運用全般に関わる各種法令、業界基準、契約上の規定を満たすための取り組みです。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"text__0":{"id":"text-9c30c25e0f","text":"\u003Cp\u003E多くの組織は、\u003Ca href=\"https://www.snowflake.com/ja/data-governance/\" target=\"_self\"\u003Eデータガバナンス\u003C/a\u003Eとコンプライアンスのギャップに監査のタイミングで初めて直面します。社内で定めた規定やポリシーが、現場で提出できるログや証拠データと紐づいていないことに、監査が入ってから気づくケースが多いためです。その結果発生するアクセス履歴の復元、データの責任者の確認、定義されていなかった運用ルールの文書化といった急ごしらえの対応は、事前にガバナンス体制を整えておくことで防ぐことができます。\u003C/p\u003E\r\n\u003Cp\u003Eデータガバナンスは、コンプライアンス遵守に不可欠な\u003Ca href=\"https://www.snowflake.com/en/data-governance/policy/audit/\" target=\"_self\"\u003E監査\u003C/a\u003Eを適切に記録、保存するための運用モデルや統制基盤の役割を果たします。ガバナンスプログラムが適切に運用されていれば、複数の規制フレームワークへの対応を単発で終わらせず、持続可能な業務プロセスとして定着させることができます。これにより、抽象的な法的要件を実行可能な統制ルールへと落とし込み、監査証拠の継続的な保存や、異なる規制間での統制ルールの共通利用が可能になります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_what-is-regulatory-compliance-in-the-data-context":{"id":"title-v2-aedfdac819","additionalClasses":"anchor-title anchor-title--what-is-regulatory-compliance-in-the-data-context","type":"heading2","lines":["データにおける規制コンプライアンスの定義"],":type":"snowflake-site/components/title-v2"},"text_what-is-regulatory-compliance-in-the-data-context_0_0":{"id":"text-73a1e231aa","text":"\u003Cp\u003Eデータ領域における規制コンプライアンスとは、データの収集、処理、保護、共有、保管、破棄に関する外部の法令、契約上の規定、および業界基準を満たすことを指します。GDPR、CCPA、HIPAA、PCI DSS、SOX法、DORA、NIS2指令、さらには最新のAI規制に至るまで、それぞれ要求される法的要件や業界、運用上の基準は異なります。しかし、その多くはデータ分類、アクセス制御、監査証跡、データ保持、不審・侵害対応、説明責任の証明といった、共通の統制領域に基づいています。\u003C/p\u003E\n\u003Cp\u003Eガバナンスを起点とするアプローチを取り入れることで、企業はこうした統制ルールを一度定義、構築すれば、複数の規制要件へ効率的に展開できるようになります。その結果、監査人からの提出要求を待つことなく、常に必要な監査証拠を用意しておくことが可能になります。\u003C/p\u003E\n\u003Ch3\u003Eデータガバナンスと規制コンプライアンス\u003C/h3\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_what-is-regulatory-compliance-in-the-data-context_0_1":{"id":"text-ff398626b3","text":"\u003Ctable\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003E\u003C/th\u003E\u003Cth\u003Eデータガバナンス\u003C/th\u003E\u003Cth\u003E規制コンプライアンス\u003C/th\u003E\u003C/tr\u003E\u003C/thead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003E範囲\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003E組織全体におけるデータオーナーシップ、品質、アクセス、分類、ライフサイクル、リネージ、制御をカバー\u003C/td\u003E\u003Ctd\u003E特定の法律、規制、契約、または業界の義務の対象となるデータとプロセスをカバー\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003E主な推進要因\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003Eビジネス戦略、リスク許容度、運用モデル、データ管理ニーズ\u003C/td\u003E\u003Ctd\u003E規制当局、監査人、業界団体、または法的コミットメントによって課される外部要件\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003Eオーナーシップ\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003E主にデータリーダー、ガバナンス評議会、スチュワード、プラットフォームオーナーが主導\u003C/td\u003E\u003Ctd\u003E主にコンプライアンス、法務、リスク、監査のステークホルダーが主導\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003E対象期間\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003Eデータ、システム、ビジネスユースケースの変化に応じて継続的かつ反復的に実施\u003C/td\u003E\u003Ctd\u003E施行日、監査サイクル、報告義務、新しい規制の期限に関連することが多い\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003E主な成果\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003Eデータ品質、信頼性、ユーザビリティ、一貫性、制御の向上\u003C/td\u003E\u003Ctd\u003E要求される義務への実証可能な準拠と、ペナルティリスクの軽減\u003C/td\u003E\u003C/tr\u003E\u003Ctr\u003E\u003Ctd\u003E\u003Cstrong\u003E基本姿勢\u003C/strong\u003E\u003C/td\u003E\u003Ctd\u003E問題が表面化する前に制御や標準が設計されるため、能動的なアクションが取れる\u003C/td\u003E\u003Ctd\u003E要件が組織の外部から発生するため、受動的なものになりがち\u003C/td\u003E\u003C/tr\u003E\u003C/tbody\u003E\u003C/table\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"quote_what-is-regulatory-compliance-in-the-data-context_0":{"id":"quote-item-d2049c3648","alignment":"left","layout":"simple","quoteSourceName":"Jennifer Belissent","quoteSourceTitle":"Snowflakeのプリンシパルデータストラテジスト","showQuoteIcon":true,"quote":"ガバナンス制御が真に効果を発揮するのは、バリューチェーン全体に及んでいる場合のみです。つまり、保存されているデータだけでなく、利用されている最中のデータまで保護されて初めて意味をなします","showHangingPunctuation":false,":type":"snowflake-site/components/quote-item"},"title_how-data-governance-enables-regulatory-compliance":{"id":"title-v2-0dce68449b","additionalClasses":"anchor-title anchor-title--how-data-governance-enables-regulatory-compliance","type":"heading2","lines":["データガバナンスが規制コンプライアンスを可能にする仕組み"],":type":"snowflake-site/components/title-v2"},"text_how-data-governance-enables-regulatory-compliance_0":{"id":"text-0bf684cacc","text":"\u003Cp\u003Eガバナンスとコンプライアンスの密接な関係を理解するには、\u003Cb\u003Eポリシー → 制御 → 監査証跡 → 証拠\u003C/b\u003Eという一連の運用プロセスを全体的な軸として捉えると分かりやすくなります。\u003C/p\u003E\r\n\u003Cp\u003E法的要件や規制要件は通常、法令、業界基準、契約書、あるいは監査フレームワークに記載された文章から始まります。データチームは、その文章を具体的な判断や運用ルールに落とし込まなければなりません。例えば、どの列に個人データが含まれているか、どのテーブルに保護対象医療情報（PHI）があるか、どの権限であれば暗号化されていない平文データを参照できるか、地域ごとにどの行を表示させるか、データをいつまで保管するか、例外処理の承認権限は誰にあるか、といった判断です。\u003C/p\u003E\r\n\u003Cp\u003Eデータガバナンスは、こうした一連の判断や設定内容を正当な記録として一元的に保持、管理する役割を果たします。たとえば、データスチュワードが特定の列を機密データとして分類し、プライバシータグの付与、責任者の定義、保管期間ルールの設定を行うと、プラットフォームチームはそれらの基準に基づいて、データマスキング、行レベルのアクセス制御、\u003Ca href=\"https://www.snowflake.com/ja/data-governance/data-security/rbac/\" target=\"_self\"\u003Eロールベースの権限管理（RBAC）\u003C/a\u003E、およびモニタリングを設定できるようになります。これにより、コンプライアンスチームは、設定された運用ルールがデータの最小化、最小権限の原則、職務分掌、データの保持・削除、インシデント対応といった、どの規制要件に対応しているのかを正確に紐づけできるようになります。\u003C/p\u003E\r\n\u003Cp\u003E監査に対する備えも、まさにこの一連のプロセスが確立されていることで実現します。監査が入ってから慌てて証拠を集めるのではなく、日常的なデータ運用の一環として、データリネージ、分類の変更履歴、アクセスログ、ポリシーの変更履歴、承認記録などを自動的に保存しておくことができます。これによって監査対応の負担がゼロになるわけではなく、法的な解釈や検討が不要になるわけでもありません。しかし、監査人から提出を求められる前に必要な監査証跡やポリシー履歴、承認ログが揃っている状態をつくれるため、証拠収集のスピードと信頼性は大幅に向上します。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ci\u003EDraftKingsが大規模な規制コンプライアンスをどのように推進しているかをご覧ください：\u003C/i\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"yt_how-data-governance-enables-regulatory-compliance_0":{"id":"embed-baa61cb5d4","youtubeVideoId":"F01IEeM3I-Y","layout":"responsive","youtubeAspectRatio":"56.25","youtubeAutoPlay":false,"youtubeLoop":false,"youtubeMute":false,"youtubePlaysInline":false,"youtubeRel":false,"embeddableResourceType":"core/wcm/components/embed/v1/embed/embeddable/youtube","type":"EMBEDDABLE",":type":"snowflake-site/components/youtube"},"title_what-regulations-require-of-your-data":{"id":"title-v2-b5696ef996","additionalClasses":"anchor-title anchor-title--what-regulations-require-of-your-data","type":"heading2","lines":["各種規制がデータに求める要件"],":type":"snowflake-site/components/title-v2"},"text_what-regulations-require-of-your-data_0_0":{"id":"text-844b87450f","text":"\u003Cp\u003E各規制は、その言語表現、対象範囲、および適用、執行モデルにおいてそれぞれ異なりますが、データに関して求めている本質的な問いは、多くの場合共通しています。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003Eどのようなデータを保有しているか\u003C/li\u003E\n\u003Cli\u003Eそのデータはどこに保管され、どのように利用されているか\u003C/li\u003E\n\u003Cli\u003E誰がアクセス権限を持っているか\u003C/li\u003E\n\u003Cli\u003E機密データはどのように保護されているか\u003C/li\u003E\n\u003Cli\u003Eどのくらいの期間、データを保持するか\u003C/li\u003E\n\u003Cli\u003E変更、障害、またはアクセスが発生した際、何が起きたかを証明できるか\u003C/li\u003E\n\u003Cli\u003E個人、規制当局、監査人、または顧客から証明を求められた際、適切に対応できるか\u003C/li\u003E\n\u003C/ul\u003E\n\u003Cp\u003Eこれらの問いに十分に応えるためには、共通した一連のコントロールファミリーを整備しておく必要があります。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_what-regulations-require-of-your-data_0_1":{"id":"text-fd164e20c4","text":"\u003Cul\u003E\n\u003Cli\u003E\u003Cstrong\u003Eデータ分類とインベントリ：\u003C/strong\u003E企業が適切なポリシーを適用するには、その前提として、個人データ、決済データ、医療データ、財務報告用データ、業務上不可欠なデータ、その他の機密データを特定しておく必要があります。また、データの分類は、対応すべき規制要件の適用範囲を明確にする上でも役立ちます。例えば、顧客ID、取引履歴、保護対象医療情報（PHI）が含まれるテーブルと、集計済みの運用メトリクスのみが含まれるテーブルとでは、求められる管理要件が異なるためです。\u003C/li\u003E\n\u003Cli\u003E\u003Cstrong\u003Eアクセス制御とポリシーの適用：\u003C/strong\u003E多くの規制では、適切な権限を持つ担当者のみが必要な目的に応じてアクセスできるよう、適切な制御を行うことが求められます。最小権限の原則、ロールベースのアクセス制御（RBAC）、データマスキング、行レベルの制限、および承認ワークフローといった仕組みを導入することで、この原則を実行可能な統制ルールとして落とし込むことができます。\u003C/li\u003E\n\u003Cli\u003E\u003Cstrong\u003E監査証跡と証明：\u003C/strong\u003Eコンプライアンスの運用には、誰が、いつデータにアクセスしたか、何が変更されたか、どの統制ルールが適用されたかを示す記録が不可欠です。こうした監査証跡は、外部への証明や報告だけでなく、インシデント発生時の原因調査や社内の内部統制においても重要な役割を果たします。\u003C/li\u003E\n\u003Cli\u003E\u003Cstrong\u003Eデータの保持と廃棄：\u003C/strong\u003Eプライバシー関連法、財務・医療規制、各種業界ルールでは、特定の記録を一定期間保持することや、不要になったデータを確実に廃棄することを義務付けています。ガバナンス体制を整えることで、廃棄の判断を現場の都度の判断に委ねるのではなく、データの種別、所有者、ライフサイクルポリシーに基づいて、保持・廃棄のロジックをシステム上で自動的に紐付けることが可能になります。\u003C/li\u003E\n\u003Cli\u003E\u003Cstrong\u003E不審、侵害発生時の対応ワークフロー：\u003C/strong\u003Eセキュリティインシデントが発生した際、担当チームは影響を受けたデータ、関連するシステム、アクセス権限の保有者、および必要となる通知手順を迅速に把握する必要があります。データ分類、データリネージ、およびアクセス履歴が整備されていれば、セキュリティ、法務、コンプライアンスの各チームは、単なる一般的なインシデント対応から、対象データに特化した具体的な対応手順へとスムーズに移行できます。\u003C/li\u003E\n\u003C/ul\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_what-regulations-require-of-your-data_0_2":{"id":"text-6a37eb97c3","text":"\u003Cp\u003Eこの共通のコントロールレイヤーが存在することで、単一のガバナンスプログラムで複数の規制要件へ同時に対応することが可能になります。適用される法的義務によって用語やラベルが変わることはあっても、どのようなデータを保有しているか、どのように制御されているか、その制御が意図通り機能したことを示す証拠はあるかを企業が把握しなければならないという本質は変わりません。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_data-privacy-regulations":{"id":"title-v2-9e651e7cb0","additionalClasses":"anchor-title anchor-title--data-privacy-regulations","type":"heading2","lines":["データプライバシー規制"],":type":"snowflake-site/components/title-v2"},"text_data-privacy-regulations_0_0":{"id":"text-f21ed66daf","text":"\u003Cp\u003Eデータプライバシー規制は、単にシステムのセキュリティを保つことにとどまらず、個人が自身のデータに対して持つ権利そのものに焦点を当てています。たとえば、顧客情報、従業員データ、端末識別子などがマーケティング、カスタマーサポート、AI処理といった業務フローを通過する際、企業はそのデータがどこに存在し、どのような目的で処理され、誰がアクセスでき、いつまで保持すべきかを正確に把握しておく必要があります。\u003C/p\u003E\r\n\u003Cp\u003Eこうしたデータ管理の考え方は日本国内だけでなくグローバル共通の要件であり、海外展開やグローバル企業のデータ移行においては、各国や地域の厳格なデータ法規制への適応が不可欠となります。\u003C/p\u003E\r\n\u003Ch3\u003EGDPR（EU一般データ保護規則）\u003C/h3\u003E\r\n\u003Cp\u003EEU一般データ保護規則（GDPR）は、EU域内における個人データの処理を規定しており、適法性、公正性、透明性、目的の制限、データの最小化、正確性、保存期間の制限、完全性と機密性、そしてアカウンタビリティといった原則を定めています。ガバナンス体制を整備することで、個人データの特定、処理目的や文脈の明確化、アクセス制限、保持ポリシーの適用、さらには説明責任を証明するための監査証跡の保存を確実に行えるようになります。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ja/data-governance/regulatory-compliance/gdpr/\" target=\"_self\"\u003EGDPRの詳細を読む →\u003C/a\u003E\u003C/p\u003E\r\n\u003Ch3\u003ECCPAおよびCPRA\u003C/h3\u003E\r\n\u003Cp\u003Eカリフォルニア州消費者プライバシー法（CCPA）は、同州の消費者に対し、自身の個人情報に関する開示請求権、削除請求権、ならびに第三者への販売・共有や特定の利用に対するオプトアウト権などの権利を保障しています。さらに、2023年1月1日に施行されたカリフォルニア州プライバシー権利法（CPRA）によってCCPAが改正、拡張され、センシティブ情報に関する新たな義務の追加や、専門機関であるカリフォルニア州プライバシー保護庁（CPPA）の設立などが盛り込まれました。ガバナンスプログラムを整備することで、センシティブ情報の正確な分類、適切なアクセス制限の徹底、そして事前開示した利用目的に沿ったデータ活用の管理が可能となり、CCPAおよびCPRAが求める法的要件を確実にクリアできるようになります。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ja/data-governance/regulatory-compliance/ccpa/\" target=\"_self\"\u003ECCPAおよびCPRAの詳細を読む →\u003C/a\u003E\u003C/p\u003E\r\n\u003Ch3\u003ELGPD（ブラジルの一般データ保護法）\u003C/h3\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_data-privacy-regulations_0_1":{"id":"text-2d2b3ea175","text":"\u003Cp\u003Eブラジルの一般データ保護法（LGPD）は、個人データの処理を対象としており、適法な処理根拠、データ主体の権利、セキュリティおよびアカウンタビリティの要件など、GDPRと共通する概念を数多く備えています。データ分類、同意状況の追跡、アクセス制御、および保持ポリシーを導入することで、自社のデータシステム全般においてこれらの法的義務を実務レベルへ落とし込むことができます。\u003C/p\u003E\n\u003Ch3\u003EPDPA（シンガポールやタイなどの個人データ保護法）\u003C/h3\u003E\n\u003Cp\u003Eシンガポールやタイなどの国や地域で施行されている個人データ保護法（PDPA）でも、企業に対して責任ある個人データ管理を求めており、一般的に事前通知、同意取得、目的制限、データ保護、保持期間の遵守、アクセス権の保障」といった規定が含まれています。ガバナンスプログラムを整備することで、これらの法的要件を、データの棚卸し、ロールベースの権限管理（RBAC）、データマスキング、ライフサイクル管理といった具体的な運用ルールと確実に紐付けることが可能になります。\u003C/p\u003E\n\u003Ch3\u003EPOPIA（南アフリカの個人情報保護法）\u003C/h3\u003E\n\u003Cp\u003E南アフリカの個人情報保護法（POPIA）は個人情報の処理を規定しており、アカウンタビリティ、処理の制限、目的の特定、セキュリティ保護措置、データ主体の関与といった要件を定めています。ガバナンス体制を整備することで、処理目的や背景の文書化、データ責任者の割り当て、保護ルールの適用、ならびに監査証跡の保存を確実に行えるようになります。\u003C/p\u003E\n\u003Ch3\u003EPIPL（中国の個人情報保護法）\u003C/h3\u003E\n\u003Cp\u003E中国の個人情報保護法（PIPL）も同様に個人情報の処理を規制しており、同意取得、透明性の確保、目的制限、データ主体の権利保証、センシティブ情報の扱い、さらにはデータの域外移転に関する厳格な規定を盛り込んでいます。ガバナンス機能を活用することで、個人データの正確な分類、処理目的の追跡管理、アクセス制御の適用、そしてデータの移転や共有に関する意思決定の履歴管理をスムーズに進められます。\u003C/p\u003E\n\u003Ch3\u003EDPDP（インドの2023年デジタル個人データ保護法）\u003C/h3\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_data-privacy-regulations_0_2":{"id":"text-ff994fcd9e","text":"\u003Cp\u003Eインドで制定された2023年デジタル個人データ保護法（DPDP法）は、個人の権利保護と正当な目的によるデータ利活用の双方に配慮した処理フレームワークを構築しました。企業が対応すべきガバナンスの本質は他の法令と共通しています。デジタル個人データを正しく特定および保護し、事前に定めた目的の範囲内で利用、保持するとともに、個人の権利行使や組織としての説明責任に対応できる運用フローへ組み込むことが求められます。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_financial-services-and-operational-resilience-regulations":{"id":"title-v2-57ae3762c9","additionalClasses":"anchor-title anchor-title--financial-services-and-operational-resilience-regulations","type":"heading2","lines":["金融サービスと重要業務の継続性（オペレーショナルレジリエンス）に関する規制"],":type":"snowflake-site/components/title-v2"},"text_financial-services-and-operational-resilience-regulations_0_0":{"id":"text-142048e5fd","text":"\u003Cp\u003E金融機関向けの規制では、財務報告やレポートの正確性、重要業務の継続性（オペレーショナルレジリエンス）、ならびに複雑なデータ、システム環境全体において統制ルールが適切に機能していることを証明する能力が求められます。リスクモデル、自己資本の計算、取引報告、オペレーショナルレジリエンスのダッシュボードなどは、多岐にわたるシステムからデータを収集、集約して作成されます。そのため、コンプライアンスの遵守には、データリネージ、統制ルールのマッピング、アクセス履歴、データ品質、およびデータ責任者の明文化が不可欠です。\u003C/p\u003E\r\n\u003Cp\u003E金融データの管理環境が分散、複雑化すればするほど、報告、アナリティクス、リスク管理、サードパーティの監視、業務継続性の確保に至るまで、共通した一貫性のあるガバナンス基盤を維持することが重要になります。\u003C/p\u003E\r\n\u003Ch3\u003EDORA（EUのデジタル運用耐性法）\u003C/h3\u003E\r\n\u003Cp\u003EEUの\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://www.eiopa.europa.eu/digital-operational-resilience-act-dora_en\"\u003Eデジタル運用耐性法（DORA）\u003C/a\u003Eは、金融機関およびそれらを支えるサードパーティのICT（情報通信技術）事業者を対象とした規制です。ICTに関する障害や障害発生時において、その影響に耐え、適切に対応し、迅速に復旧できる能力の確保に焦点を当てています。DORAは2025年1月17日に適用開始となりました。ガバナンス体制を整備しておくことで、どのデータやシステム、サードパーティへの依存関係が重要な業務を支えているのかを把握しやすくなります。また、アクセス権限の管理方法をクリアにし、インシデント対応、障害テスト、さらには監督や統制に必要なログや証跡をいつでも提示できる状態を整えることができます。\u003C/p\u003E\r\n\u003Ch3\u003ESOX（サーベンス・オクスリー法）\u003C/h3\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_financial-services-and-operational-resilience-regulations_0_1":{"id":"text-2c247b2fd8","text":"\u003Cp\u003Eサーベンス・オクスリー法（SOX法 / 米国企業改革法）は、財務報告の信頼性向上と内部統制の確立に重点を置いています。データチームにとってSOX法に関連する統制項目とは、財務報告や決算作業、監査証跡の提出を支えるシステム、データフロー、およびアクセス権限の管理を指します。ガバナンスを整備することにより、信頼できるデータソースの特定、データリネージの文書化、職務分掌の徹底、そして主要な財務報告データの変更履歴の保存を確実に行うことができます。\u003C/p\u003E\r\n\u003Ch3\u003EBasel III（バーゼルIII）\u003C/h3\u003E\r\n\u003Cp\u003EバーゼルIIIは、自己資本比率の適正性、ストレステスト、および流動性リスク管理に関する国際的な銀行規制基準です。これはデータ専用の規制ではありませんが、その厳格な運用には、リスク量、与信、流動性、自己資本に関する高精度なデータの存在が不可欠となります。ガバナンスを整えることで、金融機関は信頼できるデータソースの定義、データ品質の維持、データ加工や変換プロセスの文書化、そして再現性と信頼性の高いレポート作成プロセスの確立を実現できます。\u003C/p\u003E\r\n\u003Ch3\u003EBCBS 239（リスクデータ集計とリスク報告に関する原則）\u003C/h3\u003E\r\n\u003Cp\u003EBCBS 239は、リスクデータの集計およびレポート作成における基本原則を定めた規制基準です。この基準は、リスク報告プロセス全体を通じてデータの正確性、完全性、適時性、柔軟性、そしてトレーサビリティを強く求めるため、ガバナンスと特に深い関連性を持ちます。データリネージの可視化、データ責任者の明確化、データ品質のモニタリング、監査証跡の保存といったガバナンス機能を組み込むことで、こうした厳しい規制要件への確実な対応が可能になります。\u003C/p\u003E\r\n\u003Ch3\u003EAPRA CPS 234\u003C/h3\u003E\r\n\u003Cp\u003Eオーストラリアの金融監督庁（APRA）が定めるCPS 234は、規制対象となる金融機関等に対して情報セキュリティ管理を義務付ける基準です。情報資産の特定、統制の有効性確保、インシデント発生時の通知、およびサードパーティ管理といった要件が求められます。データガバナンスを整備することで、機密データや重要度の高いデータ資産の特定、データ責任者の明確化、アクセス制御の適用、そして統制ルールが適切に機能していることを示す監査証拠の保存を確実に行えるようになり、CPS 234への対応を強力に支援します。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_financial-services-and-operational-resilience-regulations_0":{"id":"text-2b89c030c1","additionalClasses":"callout callout--warning","text":"\u003Cp\u003E\u003Cstrong\u003Eよくある落とし穴\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003E多くの組織では、規制コンプライアンスを業務上の重要な規律としてではなく、単なる書類作成の事務作業として捉えがちです。たとえ明文化したポリシーが存在していても、具体的な統制ルールの紐づけ、データ責任者の明確化、アクセスログの取得、ならびに監査証拠の保存が行われていなければ、いざ監査人から根拠や証拠の提示を求められた際に、チームは慌てて対応に追われることになります。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular text-color-text-05"},"title_healthcare-and-payment-data-regulations":{"id":"title-v2-68e9db6e3e","additionalClasses":"anchor-title anchor-title--healthcare-and-payment-data-regulations","type":"heading2","lines":["医療および決済データに関する規制"],":type":"snowflake-site/components/title-v2"},"text_healthcare-and-payment-data-regulations_0":{"id":"text-35aa8b0233","text":"\u003Cp\u003Eコンプライアンス義務の中には、広範なプライバシー法規制や財務報告フレームワークではなく、組織が取り扱う機密データの種類そのものによって規定されるものもあります。たとえば、HIPAA（米国医療保険の相互運用性と説明責任に関する法）は保護対象医療情報（PHI）に適用され、PCI DSSはクレジットカード会員データの管理環境に適用されます。いずれの場合も、遵守すべき本質は同じです。規制対象のデータがどこに存在し、どの権限であればアクセスでき、機密データがどのように保護されているか、そしてアクセス履歴を事後に追跡、確認できるかどうかが鍵となります。\u003C/p\u003E\n\u003Ch3\u003EHIPAA（米国医療保険の相互運用性と説明責任に関する法）\u003C/h3\u003E\n\u003Cp\u003EHIPAAは、米国のヘルスケア分野における保護対象医療情報（PHI）の取り扱いを規定する法律です。ガバナンス体制を整備することにより、PHIの特定、役職や利用目的に応じたアクセス制限、データフローの文書化、適切な保護措置の適用、ならびに機密性の高い医療データがどのようにアクセスされ利用されたかを示す監査記録の保存を確実に行えるようになります。\u003C/p\u003E\n\u003Ch3\u003EPCI-DSS（クレジットカード業界のデータセキュリティ基準）\u003C/h3\u003E\n\u003Cp\u003EPCI DSSは、カード会員情報を保存、処理、または伝送するすべての組織に適用される基準です。2024年6月にリリースされた最新版PCI DSS v4.0.1においても、PCI SSC（安全基準協議会）により、2025年3月31日に設定されていた段階的要件の完全適用期日に変更がないことが明確に示されています。ガバナンス機能を活用することで、決済部門はカード会員データ環境（CDE）の適用範囲の特定、決済データの分類、アクセス制限、アクティビティのモニタリング、そして審査および監査に必要な証拠の保管をスムーズに進めることができます。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_cybersecurity-and-data-quality-regulations":{"id":"title-v2-0e34ce34f7","additionalClasses":"anchor-title anchor-title--cybersecurity-and-data-quality-regulations","type":"heading2","lines":["サイバーセキュリティとデータ品質に関する規制"],":type":"snowflake-site/components/title-v2"},"text_cybersecurity-and-data-quality-regulations_0":{"id":"text-02a7ee05ca","text":"\u003Cp\u003E一部のコンプライアンス要件では、単一の規制対象データを管理することにとどまらず、規制業務を支えるシステム、統制、そしてデータそのものを組織が真に信頼できるかどうかに主眼が置かれています。たとえば、EUのNIS2指令は、対象セクターの企業や組織に対してサイバーセキュリティリスク管理とインシデント報告の義務を課しています。一方で、ISO 8000はデータ品質に関する国際規格であり、より立証性が高く信頼できるレポート作成、監査対応、および証拠保全プロセスの構築を支援します。\u003C/p\u003E\n\u003Ch3\u003ENIS2（EUの第2次ネットワーク・情報システム指示書）\u003C/h3\u003E\n\u003Cp\u003EEUのNIS2指令（第2次ネットワーク・情報システム指示書）は、EU域内の重要分野および主要分野に渡りサイバーセキュリティ要件を拡大、強化するものです。加盟国には2024年10月17日までの国内法化が義務付けられ、翌10月18日より適用開始となりました。データガバナンスを整備することにより、必須サービスに紐づくデータやシステムの特定、インシデント対応ワークフローの支援、ならびにアクセス権限、責任者、統制範囲の文書化をスムーズに行えるようになります。\u003C/p\u003E\n\u003Ch3\u003EISO 8000（データの品質とデータ交換に関する国際規格）\u003C/h3\u003E\n\u003Cp\u003EISO 8000は、データの品質とデータ交換に関する国際規格です。コンプライアンスを目的としたデータ管理プログラムにおいて、ISO 8000は極めて重要な役割を果たします。規制対応で提出する証拠の正当性は、その根拠となるデータの品質に依存するためです。データ所有者の明確化、データ定義の統一、品質ルールの策定、データリネージの可視化、および課題管理を徹底することで、各種レポート、監査対応、証明におけるデータの信頼性を担保できます。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_ai-data-governance-regulations-and-frameworks":{"id":"title-v2-279bcd1727","additionalClasses":"anchor-title anchor-title--ai-data-governance-regulations-and-frameworks","type":"heading2","lines":["AIデータガバナンスに関する規制とフレームワーク"],":type":"snowflake-site/components/title-v2"},"text_ai-data-governance-regulations-and-frameworks_0_0":{"id":"text-33fde70606","text":"\u003Cp\u003E組織は、自社が運用するAIシステムの正確性、バイアス、説明可能性、そしてセキュリティの正当性を説明できる準備を整えておく必要があります。これには、トレーニング、検証、テスト、あるいはグラウンディングにどのデータが使われたのか、そのデータの入手元、前処理のプロセス、そしてどのような統制ルールの下で利用されたのかまでが含まれます。\u003C/p\u003E\r\n\u003Cp\u003EデータチームにとってAIの規制対応とは、トレーニングデータ、検証データ、プロンプト、RAGなどで参照する検索ソース、さらにはモデルの出力結果に至るまで、あらゆる要素をガバナンスの効いたデータ資産として管理することを意味します。適用すべき統制ルールの根幹は従来のデータ管理と変わりませんが、コンプライアンスの対象が上流でのデータ選択によって挙動が左右されるAIシステムそのものに拡大したと言えます。\u003C/p\u003E\r\n\u003Ch3\u003EEU AI法\u003C/h3\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://artificialintelligenceact.eu/\"\u003EEU AI法\u003C/a\u003Eは、高リスクAIシステムにおいてAIのコンプライアンスとデータガバナンスが不可分であることを明確に定めています。第10条では、トレーニングデータを使用する高リスクAIシステムに対し、所定の品質基準を満たすトレーニング、検証、テスト用データセットに基づいて開発することを求めています。これには、データの収集、事前処理、バイアスの検証、欠損データの確認、さらには想定される利用文脈におけるデータの関連性や代表性の検証など、多岐にわたるデータガバナンスおよび管理プロセスを組み込むことが義務付けられています。\u003C/p\u003E\r\n\u003Ch3\u003ENIST AI RMF（NIST AIリスクマネジメントフレームワーク）\u003C/h3\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://www.nist.gov/itl/ai-risk-management-framework\"\u003ENIST AI RMF\u003C/a\u003Eは法的な規制ではありませんが、組織がAIリスクを管理するための実践的な枠組みを提供します。ガバナンス（Govern）、明確化（Map）、測定（Measure）、管理（Manage）からなる4つのコア機能により、ガバナンス方針、システムの利用文脈、定量的リスク測定、および継続的なリスク対応をシームレスに紐付けます。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"text_ai-data-governance-regulations-and-frameworks_0_1":{"id":"text-f5ad74736d","text":"\u003Cp\u003E実務において、これらの機能を有効に働かせるにはガバナンスの効いたデータの存在が不可欠です。チームには、AIシステムのユースケースを明確化し、適切なデータを用いてパフォーマンスやバイアスを測定し、データやモデルの挙動変化に伴うリスクを管理したうえで、法務・リスク管理・コンプライアンス・監査などの関係者が検証できるログや証跡を保存することが求められます。システムの構築や運用に関わるデータソース、データ加工と変換処理、アクセス制御ルール、評価用データなどを遡って追跡できない状態では、単にAIモデルインベントリを整備するだけでは不十分です。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_governance-risk-and-compliance":{"id":"title-v2-0a4196209a","additionalClasses":"anchor-title anchor-title--governance-risk-and-compliance","type":"heading2","lines":["ガバナンス、リスク、コンプライアンス（GRC）"],":type":"snowflake-site/components/title-v2"},"text_governance-risk-and-compliance_0":{"id":"text-7e924645a6","text":"\u003Cp\u003Eガバナンス、リスク、コンプライアンス（GRC）は、組織における運用基準の設定と徹底、リスクの特定と管理、そして法的および規制上の法的義務への適合の証明という、相互に関連する3つの領域を統合する枠組みです。データ管理の文脈において、GRCの実行性は、データチームが日常的に管理している運用要素（データ責任者、分類、アクセス制御、データリネージ、承認プロセス、例外処理、監査証跡など）に直接依存します。\u003C/p\u003E\r\n\u003Cp\u003EGRCプログラムがリスク分類、統制フレームワーク、レポートの運用サイクルを定義する一方で、それらを証明する根拠を提示するのはデータガバナンスの役割です。規制対象データへのアクセス制限を課す統制を運用する場合、組織はどのデータが対象か、どの権限にアクセスを認めるか、どのポリシーを適用するか、そして未処理の例外申請が残っていないかを正確に把握しておく必要があります。また、財務報告データの保存を義務付ける統制においては、データライフサイクルルールの策定、データ責任者の明確化、そしてポリシーに基づきレコードが適切に保存・破棄されたことを示す確実な証拠が不可欠となります。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ca href=\"https://www.snowflake.com/ja/fundamentals/governance-risk-compliance/\" target=\"_self\"\u003Eガバナンス、リスク、コンプライアンスの詳細はこちら →\u003C/a\u003E\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_how-one-governance-program-satisfies-many-regulations":{"id":"title-v2-44d5bf48fd","additionalClasses":"anchor-title anchor-title--how-one-governance-program-satisfies-many-regulations","type":"heading2","lines":["1つのガバナンスプログラムで多くの規制に対応する方法"],":type":"snowflake-site/components/title-v2"},"text_how-one-governance-program-satisfies-many-regulations_0":{"id":"text-1576ee580d","text":"\u003Cp\u003E規制や法的義務が複雑化、拡大するなかで、適切に運用されているガバナンスプログラムはその価値をより一層発揮します。1つの統制を整備、運用することで、複数の規制要件に同時に対応できるためです。たとえば、\u003Ca href=\"https://www.snowflake.com/ja/data-governance/data-lineage/\" target=\"_self\"\u003Eデータリネージ\u003C/a\u003Eを可視化しておくことは、財務報告の監査対応、リスクモデルの説明責任、インシデント発生時の影響範囲の分析、さらにはAIシステムの仕様文書化に至るまで、幅広い用途に活用できます。同様に、アクセス制御を適切に組み込むことで、データの機密性確保、職務分掌の徹底、最小権限の原則の適用、そしてデータの最小化という要件をまとめて充足できます。\u003C/p\u003E\r\n\u003Cp\u003E例として、HIPAA（米国医療保険の相互運用性と説明責任に関する法）、州のプライバシー関連法、社内のセキュリティポリシー、さらにはパートナー企業との契約上の義務を同時に遵守しなければならない医療機関について考えてみます。統合されたガバナンスプログラムが存在しない場合、規制や義務が追加されるたびに、個別のインベントリ作成、個別のアクセス権限レビュー、個別の監査証拠の収集が発生してしまいます。一方で、共通の統制基盤が整っていれば、PHIやその他の個人データを一度分類、定義するだけで済みます。その分類に対して責任者やポリシーを紐付け、必要に応じて動的マスキングや行レベルでのアクセス制限を適用し、データフローを文書化しておくことで、ひとつの監査証拠を複数のレビューや監査で再利用することが可能になります。\u003C/p\u003E\r\n\u003Cp\u003Eもちろん、これは1つの統制ルールで全ての規制要件を自動的にクリアできるという意味ではありません。法的解釈は依然として重要であり、適用される規制ごとに求められる閾値、作成すべきドキュメント、レビューの周期などは異なります。しかし、ガバナンスを起点としたコンプライアンス運用を構築することで、再利用可能な基盤が確立されます。既存の統制ルールと法的義務をマッピングし、監査証跡を常時保存できる状態を維持しておくことで、新たな法規制が登場した際にも自社にすでに存在する統制ルールでどこまで対応できるかを即座に評価できるようになります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_regulatory-compliance-on-snowflake":{"id":"title-v2-41b19e116a","additionalClasses":"anchor-title anchor-title--regulatory-compliance-on-snowflake","type":"heading2","lines":["Snowflakeにおける規制コンプライアンス"],":type":"snowflake-site/components/title-v2"},"text_regulatory-compliance-on-snowflake_0":{"id":"text-0b067c74f4","text":"\u003Cp\u003ESnowflakeは、メタデータ管理、ポリシーの適用、および監査可能性をデータそのものに近づけることで、組織がガバナンス統制をコンプライアンスの運用ワークフローへスムーズに組み込めるよう支援します。たとえば、\u003Ca rel=\"noopener noreferrer\" target=\"_self\" href=\"https://www.snowflake.com/ja/product/features/horizon/\"\u003ESnowflake Horizonカタログ\u003C/a\u003Eを活用することで、アクセス、マスキング、行レベルの制限、リネージ、機密データ分類の制御を含め、Snowflake全体のデータを検出、分類、ガバナンス、保護できます。\u003C/p\u003E\r\n\u003Cp\u003E\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://docs.snowflake.com/ja/user-guide/access-history\"\u003ESnowflake Access History\u003C/a\u003Eは、クエリがデータを読み取った日時や、SQL文がインサート、アップデート、デリート、コピーなどの書き込み操作を実行した日時を記録することで、運用チェーンにさらなる要素を追加します。コンプライアンスチームにとって、このアクセス履歴はポリシーの適用を監査証跡や証拠に紐付けるのに役立ちます。\u003C/p\u003E\r\n\u003Cp\u003Eさらに、\u003Ca rel=\"noopener noreferrer\" target=\"_blank\" href=\"https://trust.snowflake.com/\"\u003ESnowflake Compliance Center\u003C/a\u003Eは、スキャナーの検出結果、セキュアな認証の準備状況、\u003Ca href=\"https://www.snowflake.com/ja/data-governance/data-security/\" target=\"_self\"\u003Eデータセキュリティ\u003C/a\u003Eなど、アカウントのセキュリティ態勢に関するハイレベルなインサイトを可視化することで、態勢のモニタリングをサポートします。Snowflakeは、SOC 1 Type II、SOC 2 Type II、ISO認証などのグローバル認証を含むコンプライアンスリソースを通じて、コンプライアンスに関するドキュメントや認証も提供しており、リージョンやプログラムごとの追加のコンプライアンス情報も利用できます。\u003C/p\u003E\r\n\u003Cp\u003Eこれらの機能を組み合わせることで、組織は書面による意図からガバナンスの効いた運用へ、そしてガバナンスの効いた運用から監査、証明、規制審査をサポートする証拠へと移行できるようになります。\u003C/p\u003E\r\n","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"title_governance-makes-compliance-reusable":{"id":"title-v2-431e876d96","additionalClasses":"anchor-title anchor-title--governance-makes-compliance-reusable","type":"heading2","lines":["ガバナンスによるコンプライアンスの再利用性の向上"],":type":"snowflake-site/components/title-v2"},"text_governance-makes-compliance-reusable_0":{"id":"text-2c7cf2c6df","text":"\u003Cp\u003E規制ごとに求められる遵守要件は異なりますが、その根底にある、どのようなデータが存在し、どこへ連携され、誰にアクセス権限があり、どのように保護され、その統制が機能していることを証明できるかといった運用上の事実は、多くの場合において共通しています。\u003C/p\u003E\n\u003Cp\u003E適切に機能しているガバナンスプログラムでは、こうした運用上の事実を特別な作業としてではなく、日常のデータ運用のプロセスの中で自然に取得・記録します。データ分類、オーナーシップの明文化、データリネージ、アクセス制御ポリシー、データ保持ルール、そして監査証跡。これらを再利用可能な統制ルールとして確立しておくことで、プライバシー関連法、財務報告要件、オペレーショナルレジリエンス規制、医療や決済業界の標準規格、さらにはAIガバナンスのフレームワークに至るまで、多様な規制要件へ柔軟に紐付けることが可能になります。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-color-text-05"},"callout_governance-makes-compliance-reusable_0":{"id":"text-03a0741f34","additionalClasses":"callout callout--general","text":"\u003Cp\u003E\u003Cstrong\u003E重要なポイント\u003C/strong\u003E\u003C/p\u003E\n\u003Cp\u003Eデータガバナンスを導入することで、コンプライアンスプロセスの再現性と定着性を高めることができます。データ分類、アクセス制御ポリシー、データリネージ、保持ルール、監査証跡といった要素を再利用可能な統制ルールとして仕組み化することで、組織は複数の規制要件に一括で対応できるようになります。さらに、実際の監査が始まる前であっても、必要な監査証拠を常時維持することが可能です。\u003C/p\u003E","richText":true,":type":"snowflake-site/components/text","appliedCssClassNames":"text-size-regular 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