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aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-fe5707b215","text":"\u003Cp\u003EアナリティクスがエンタープライズAIの時代に突入するなかで、現在および将来のデータニーズのための優れた接続性と信頼性を備えた堅牢なプラットフォームを求めるお客様の要件は変わっていません。  \u003C/p\u003E\n\u003Cp\u003E「サーバーレスコンピューティング」により、お客様はハードウェアリソースやソフトウェアリソースをプロビジョニング、展開、管理することなく、クラウド機能を使用できるようになりました。Snowflakeは2012年の創業以来、サーバーレスを推進しています。データのロード、管理、クエリに必要なコードはお客様が提供し、その他の作業はSnowflakeが担当します。一部のサーバーレスプラットフォームでは、ベンダーがコンピュートを管理しているが、ストレージは管理していない場合などには、以前として単一のベンダーまたは複数のベンダーのさまざまなサービスをつなぎ合わせる必要があります。 \u003C/p\u003E\n\u003Cp\u003Eさらに、ほとんどのベンダーでは、クラスターのスピンアップやスピンダウン、中断を伴うアップグレード、コードのリファクタリング、さらにはサーバーレス機能やパフォーマンスの改善機能を利用するための新しいエディションへの移行に、貴重な時間とリソースを必要とします。ほとんどのベンダーはセキュリティとガバナンスの機能を備えていますが、包括的なソリューションを提供するためには複数のサービスの統合が求められる場合や、旧バージョンの製品では利用できないためにアップグレードを余儀なくされる場合があります。この問題は、クロスリージョンやクロスクラウドの展開を使用しているお客様において、特にサービス停止や災害の潜在的なリスクがある場合に悪化します。最後に、企業はこれまで、FTPサーバーからのファイル取得、APIスクレイピング、複雑なデータパイプラインを必要とする非効率的でレガシーなテクノロジーを使用してコラボレーションを実行してきました。こうしたプロセスは、コストと時間がかかるだけでなく、データが移動してしまうとお客様はすべての制御を失うため、ガバナンスとセキュリティのリスクももたらしました。その結果、データが活用されないことがよくありました。ベンダーによってはフェデレーション共有モデルを使用しているところもあります。これは状況によっては有効な場合もありますが、コストの予測と制御が劣る可能性があります。\u003C/p\u003E\n\u003Cp\u003E一方、Snowflakeは、創業以来サーバーレスであるだけでなく、何千社もの顧客に信頼されている、すべてのデータ資産が接続された非常に簡単なフルマネージドのサービスを提供しています。   \u003C/p\u003E\n\u003Ch2\u003ESnowflakeは簡単 \u003C/h2\u003E\n\u003Cp\u003E組織はこれまでも常に、エンドツーエンドのデータ管理とスケーラビリティによって価値実現までの時間を短縮して、差別化を図る必要がありましたが、AIへの移行の動きが進むにつれて、このニーズはさらに重要なものとなっています。生成AIなどのイノベーションを簡単に実装できるプラットフォームは必須事項です。 \u003C/p\u003E\n\u003Cp\u003E組織はデータやAIから可能な限り多くのビジネス価値を得ようと競っていますが、そうした背景の中で予算も精査されています。組織は、常により少ないコストでより多くのことを行うことを余儀なくされています。そのため、使いやすいコスト管理機能を備えた経済的なソリューションが求められています。 \u003C/p\u003E\n\u003Cp\u003ESnowflakeのフルマネージドサービスは、プラットフォーム管理を担当してデータの場所でAIを扱えるようにすると同時に、組み込みのコスト管理を備えた継続的に改善するエンジンを提供することで、お客様のために価値を最適化し続けます。これらの機能には、以下が含まれます。 \u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E自動管理：\u003C/b\u003ESnowflakeは、最小限の操作ですぐに使用できます。継続的に使用するなかで、チューニングや最適化はほとんど必要ありません。また、バキュームコマンドやその他のハウスキーピングタスクの実行などのメンテナンスタスクは、お客様の労力を必要とせず、お客様に影響を与えることもなくバックグラウンドで実行されます。これは、総保有コストに大きな影響を与えます。貴重な管理時間を節約できることからコストも節減され、新規プロダクトのローンチやデータプロジェクトの完了のためにコストを迅速に再配分できるようになります。\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eほぼ即時のスケーラビリティ：\u003C/b\u003ESnowflakeのようなフルマネージドサービスでは、ほぼ即時のスケーラビリティを実現するリソースの予備プールを利用できます。これらのリソースはベンダーのVPCで実行されるため、そのリージョンのすべてのお客様と共有でき、リソースのスケールアップやスケールダウンを簡単に行えるようになります。顧客マネージドのサービスでは、顧客は自身のテナンシーでコンピュートを実行するため、予備のプールが必要な場合はその料金を支払う必要があり、クラウドがサポートする伸縮性が無駄になります。ほとんどの顧客マネージドのプラットフォームでは、容量の追加や削除に時間がかかります。また、顧客がインスタンスを管理し、ソフトウェアをロードし、クラスターに結合する必要があります。Snowflakeであれば、すべてがほぼ瞬時に実行されます。\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E中断のないアップグレード：\u003C/b\u003ESnowflakeは、お客様の業務を中断することなく、すべてのソフトウェアバージョンのアップグレードとパッチを扱えます。アップグレードの計画、実行、検証は、ダウンタイムのないローリングプロセスを使用して行います。これは、すべてのお客様が同じソフトウェア上で同じ機能を使用して実行することを意味します。サービスとしてのプラットフォーム（PaaS）のオファリングに関するドキュメントにはよく、サービスの特定のバージョンではサポートされていない機能や、計画的なメンテナンスのための停止時間が記載されていますが、Snowflakeではこうした問題はありません。\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E組み込みのAI：\u003C/b\u003ESnowflakeは、お客様のデータの場所でAIを利用できるようにします。お客様は、Snowflake ArcticやAnthropicのClaudeなどのモデルを活用し、Snowflakeの生成AI機能であるSnowflake Cortex AIを通じてテキスト処理、感情分析、カスタム要約などのタスクを実行できるようになります。SQLやPythonなどの複数のコードインターフェイスに簡単にアクセスでき、Snowflake AI & ML Studioを使用してノーコード開発を行うことも可能です。Cortex AIからは、生成AI製品スイートも誕生しています。たとえば、Snowflake内でのタスクの完了を支援するAI駆動のアシスタントであるSnowflake Copilotや、機械学習によってさまざまなタイプのドキュメントのデータを理解して抽出するサービスファミリーのDocument AIなどです。\u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E使いやすいインターフェイスによるコストの可視化、制御、最適化：\u003C/b\u003ESnowflakeのコスト管理インターフェイスには、アカウントと組織の概要が表示され、最もコストのかかるクエリなどの費用や使用状況のメトリックを詳細なドリルダウンで簡単に追跡できます。さらに、Snowflakeクレジットの価値が時間の経過とともにどのように変化していくかを示します。お客様は、インターフェイス上でリソースモニターを使用してSnowflakeの費用を制御し、クレジットの使用限度額の設定、通知の受領、指定した限度額に近づいたり超過したりした仮想ウェアハウスへの措置を行えます。Budgetsは、インターフェイスの費用を制御するためのもう一つの機能です。ユーザーは、アカウントレベルまたはクレジット消費リソースのカスタムグループで費用の限度額を指定し、限度額の超過が予想される場合に通知を受け取ることができます。さらに、インターフェイスのコストインサイトにより、最近クエリされていない大きなテーブルなど、コスト削減の機会が明らかになり、リソース使用率が最適化されます。 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E自動的なパフォーマンス改善：\u003C/b\u003Eまた、Snowflakeではクエリ時間やクエリ処理における定期的なパフォーマンス強化を自動的にロールアウトしており、お客様は介入なしにこのメリットを享受できます。実際のお客様が経験しているSnowflakeのパフォーマンスのこのような改善は、\u003Ca href=\"https://www.snowflake.com/en/data-cloud/pricing/performance-index/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflakeパフォーマンス指数（SPI）\u003C/a\u003Eで定期的に追跡できます。実際、過去26か月間で、Snowflakeはクエリ時間を40%改善しました。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch2\u003ESnowflakeは接続されている \u003C/h2\u003E\n\u003Cp\u003Eデータチームと開発者は、データのコピーと移動のためのインフラストラクチャの構築に膨大な時間を費やしています。この課題は、データ量の増加、規制当局の監視、必要なデータすべてが1つの組織内にあるわけではないという事実によって悪化しています。データから得られるインサイトとビジネス価値を最大化するには、チームは組織内の他のメンバーだけでなく、パートナー、ベンダー、さらには顧客とも迅速かつ簡単にデータコラボレーションを行う必要があります。また、サードパーティから購入したいデータプロダクトを特定し、そのプロダクトの評価、支払い、統合を簡単に行える必要があります。 \u003C/p\u003E\n\u003Cp\u003E機敏さを保ち、ワークストリームごとに最適なツールを柔軟に利用するためには、特定のベンダーやテクノロジーへのロックインを回避する必要があります。代わりに、複数のクエリエンジンや変換エンジンが同一のデータで取り込みや変換を行うことなく動作できるよう、相互運用性のあるオープンなデータフォーマットを中心にデータエコシステムを構築する必要があります。 \u003C/p\u003E\n\u003Cp\u003ESnowflakeの中核は、ゼロETL共有とオープンテーブルフォーマットによる相互運用性によって実現する、豊かなデータエコシステムです。お客様は、すべてのデータ、アプリ、モデルから最大限の価値を引き出すことができるようになります。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eシームレスなデータ共有：\u003C/b\u003ESnowflakeは、リージョンやクラウドをまたいだモダンなアクセス制御ベースのテクノロジーにより、データ移動の不要なプライバシー重視のデータ共有を実現したパイオニアです。Snowflakeの共有機能は、SaaSアプリケーションのゼロコピー統合にまで拡張されています。また、Snowflake Cortex SearchとSnowflake Intelligenceの機能にも拡張され、MLモデルやナレッジ拡張をサポートしています。 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E社内外のセキュアなコラボレーション：\u003C/b\u003ESnowflakeでは、お客様は1回のUniversal Searchで、組織の内外から、ダッシュボード、ワークシート、データ、モデル、アプリ、ドキュメントを簡単に検索してアクセスできます。さらに、インターナルマーケットプレイスを通じて組織内の他のチームから、またはSnowflakeマーケットプレイスを通じて18以上のカテゴリーの680以上のパートナーやベンダーから、データ、アプリ、AIプロダクトを探索して統合することも可能です。お客様は、Snowflakeマーケットプレイスを介した直接購入により、データとアプリケーションの調達を加速できます。既存のSnowflakeキャパシティコミットメントも使用できます（現時点では米国のみ）。 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003E相互運用可能なストレージ：\u003C/b\u003ESnowflakeは、サイロや遅延を発生させることなく、構造化データ、半構造化データ、非構造化データへのシームレスなアクセスと処理を可能にします。デフォルトの暗号化、組み込みのストレージ圧縮、ペタバイト規模でも高速なデータアクセスなど、ユニークな自動化と最適化の機能を備えています。Snowflakeの柔軟性は、データレイク、データウェアハウス、レイクハウス、データメッシュなど、さまざまなアーキテクチャパターンの展開を可能にします。オンプレミスデータや、Apache Icebergなどのオープンテーブルフォーマットとの互換性があるため、Snowflakeの価値が組織のすべてのデータ資産に広がります。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch2\u003ESnowflakeは信頼できる\u003C/h2\u003E\n\u003Cp\u003E近年では、包括的なセキュリティ、ガバナンス、事業継続性が最重要事項になっていますが、企業が新たなAIユースケースへと拡大し、リージョンやクラウドをまたいでデータファブリックやメッシュを構築するにつれて、信頼性がますます重要になっています。 \u003C/p\u003E\n\u003Cp\u003ESnowflakeのフルマネージドサービスは、リージョンやクラウドの垣根を越えて統合されたセキュリティ、ガバナンス、事業継続性/ディザスタリカバリを実現する、すぐに実証可能なエンタープライズ級の信頼を得ています。\u003C/p\u003E\n\u003Cul\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eすぐに利用可能なSnowflake Horizonカタログ：\u003C/b\u003ESnowflake Horizon Catalogを使用すると、セキュリティ管理者と最高情報セキュリティ責任者は、クラウドをまたいで一貫したアクセス制御を実装し、クロスクラウドのセキュリティリスクを迅速に特定して解決できるようになります。また、データガバナーとデータスチュワードは、実証された組み込みのガバナンス保護を機密コンテンツに簡単に適用できます。データチームは、エコシステム全体にわたって、ガバナンスの効いたデータ、アプリ、モデルを迅速に検索、発見、アクセス、共有し、プライバシー重視のコラボレーションを強化できます。Horizon Catalogの高度な機能は、Snowflake Open Catalog内の他の互換エンジンで作成されたApache Iceberg™テーブルを、統合してSnowflakeに同期した後に拡張することもできます。 \u003C/p\u003E\n\u003C/li\u003E\n\u003Cli\u003E\u003Cp\u003E\u003Cb\u003Eすぐに実現できる事業継続性/ディザスタリカバリ：\u003C/b\u003ESnowflakeを利用することで、お客様はミッションクリティカルなアカウントとデータセットを簡単に保護し、アップタイムを維持できます。ストレスイベントの際やビジネス戦略の変化に応じて任意に、リージョンやクラウドにまたがってデータベース、アカウント、パイプラインなどを1つの場所からシームレスに複製や同期を実行することで、弾力性、レジリエンシー、フェイルオーバーを確保します。\u003C/p\u003E\n\u003C/li\u003E\n\u003C/ul\u003E\n\u003Ch2\u003ESnowflakeプラットフォームのパワー\u003C/h2\u003E\n\u003Cp\u003E多くの企業のバイヤーは、機能や価格設定の違いのみに注目して、自社のニーズを満たす適切なデータプラットフォームを選ぼうと苦闘しています。しかし、ここまでに説明してきたすべての自動化やすぐに利用可能な機能の価値を考慮すると、フルマネージドのサービスと顧客マネージドのサービス（「サーバーレス」のサービスも含む）の比較は複雑化します。顧客マネージドのサービスでは、組織はこれらの機能を自分たちで計画、実装、管理することを想定する必要があります。そのため、TCOを計算する際には、これらの機能を管理するためのリソースの雇用、トレーニング、専門化に必要な追加の時間、労力、コストをすべて織り込む必要があります。そうしなければ、プロダクトの立ち上げやデータプロジェクトの完了にかかる時間を短縮できないからです。多くの場合、このような追加コストが発生するため、顧客マネージドのソリューションの運用にかかる総コストは、フルマネージドサービスにかかるコストよりもはるかに高くなります。\u003C/p\u003E\n\u003Cp\u003Eそれに対し、Snowflakeは10年以上にわたり、使いやすさ、接続性、信頼性を念頭に置いて構築されたフルマネージドサービスを提供し、お客様があらゆるテクノロジーの動きに対処できるように支援してきました。SnowflakeがデータとAIのニーズをどのように変革したかについて、Snowflakeのお客様であるPfizerとOM1は以下のように話しています。\u003C/p\u003E\n\u003Cp\u003E「Snowflakeは、当社のデータファウンデーションを戦略的に簡素化してくれました。これにより、同時実行性やデータサイロの問題をエンタープライズ規模で解決できました。Snowflakeは使いやすくメンテナンスが不要であるため、データベース管理業務が大幅に削減されます。「他にはない機能を利用でき、コストも削減できました。……今では、さまざまなビジネスユニットがデータを共有する必要が生じた場合でも、データはすべてコンプライアンスとセキュリティが確保された信頼できる1つの場所に一元化されています。当社が「One Pfizer」を実現するうえで、Snowflakeは大いに貢献してくれました」\u003C/p\u003E\n\u003Cp\u003E—Steve Ring氏（Pfizer、Enterprise Database Solutions担当Director）\u003C/p\u003E\n\u003Cp\u003E\u003Ca rel=\"nofollow noopener noreferrer\" href=\"https://www.snowflake.com/en/customers/all-customers/case-study/pfizer/\" target=\"_blank\"\u003EPfizerのSnowflakeジャーニーの詳細はこちら\u003C/a\u003E\u003C/p\u003E\n\u003Cp\u003E「私たちは、エコシステム全体をシンプルにするというミッションに取り組んでいました。データはSnowflakeに移行していましたが、当社のコンピュートエコシステムは、AWS、Databricks、カスタムソフトウェアにわたって広がる複雑なものでした。このシステムは適切に機能していましたが、かなりのコストとオーバーヘッドを伴いました。ビジネスの視点で見ると、重要なのは効率性です。私たちは、データエンジニアに対し、プラットフォームのメンテナンスではなく、イノベーションと難しい問題の解決に時間を割いてほしいと考えています。エコシステムを簡素化するために、OM1はデータ処理を従来のプラットフォームからSnowflakeへと移行し、そのプロセスで効率性、コスト削減、パフォーマンス改善を実現しました」\u003C/p\u003E\n\u003Cp\u003E—Eric Schrock氏（OM1、CTO）\u003C/p\u003E\n\u003Cp\u003E\u003Ca rel=\"nofollow noopener noreferrer\" href=\"https://www.snowflake.com/en/customers/all-customers/case-study/om1/\" target=\"_blank\"\u003EOM1のSnowflakeジャーニーの詳細はこちら\u003C/a\u003E\u003C/p\u003E\n\u003Cp\u003E \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":{"columnClassNames":{"premium_content_bann":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-responsive-component-top-padding-medium",":items":{"premium_content_bann":{"id":"premium-content-banner-f8cfdabacf","contentEyebrow":"eBook","contentHeadline":"The Essential Guide to Cloud AI and Data 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