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Dataflow シリーズの最後のコースでは、Dataflow 運用モデルのコンポーネントを紹介します。パイプラインのパフォーマンスのトラブルシューティングと最適化に役立つツールと手法を検証した後で、Dataflow パイプラインのテスト、デプロイ、信頼性に関するベスト プラクティスについて確認します。最後に、数百人のユーザーがいる組織に対して Dataflow パイプラインを簡単に拡張するためのテンプレートについても確認します。これらの内容を習得することで、データ プラットフォームの安定性を保ち、予期せぬ状況に対する回復力を確保できるようになります。

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What's inside

Syllabus

はじめに
このモジュールではコースの概要を説明します。
モニタリング
このモジュールでは、ジョブリストのページを使用して、モニタリングまたは調査を行うジョブをフィルタする方法を学習します。ジョブグラフ、ジョブ情報、ジョブの指標の各タブがどのように連携して Dataflow ジョブの包括的な概要を提供しているかを見ていきます。最後に、Dataflow と Metrics Explorer との統合を利用して、Dataflow 指標のアラート ポリシーを作成する方法を学びます。
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ロギングと Error Reporting
このモジュールでは、ジョブグラフ ページとジョブの指標ページの両方の下部にあるログパネルの使用方法と、一元化されたエラーレポート ページについて学習します。
トラブルシューティングとデバッグ
このモジュールでは、Dataflow パイプラインのトラブルシューティングとデバッグの方法を学習します。また、Dataflow における 4 つの一般的な障害モード(パイプラインの構築に関する障害、Dataflow でのパイプラインの開始に関する障害、パイプライン実行中の障害、パフォーマンスの問題)についても確認します。
パフォーマンス
このモジュールでは、Dataflow でバッチ パイプラインとストリーミング パイプラインを開発する際に配慮すべきパフォーマンスの注意事項について説明します。
テストと CI / CD
このモジュールでは、Dataflow パイプラインの単体テストについて説明します。また、Dataflow パイプラインの CI / CD ワークフローを合理化するために利用できるフレームワークと機能も紹介します。
信頼性
このモジュールでは、破損したデータやデータセンターの停止に対して復元性の高いシステムを構築する方法について説明します。
Flex テンプレート
このモジュールでは、Flex テンプレートについて説明します。Flex テンプレートは、データ エンジニアリング チームが Dataflow パイプライン コードを標準化して再利用するのに役立つ機能であり、このテンプレートを使用すると、運用上の多くの課題を解決できます。
まとめ
このモジュールでは、コースで扱ったトピックを再確認します。

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
学んだことを基にデータプラットフォームの安定性強化と予期せぬ状況に対する回復力の向上が図れる
Dataflowの可用性、パフォーマンス、信頼性を向上させるための実用的な手法を学ぶ
Google Cloud Trainingが提供する信頼性の高い情報

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Serverless Data Processing with Dataflow: Operations - 日本語版 with these activities:
コース資料を整理する
コース資料を整理することで、重要な概念を強調し、理解を深めます。
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  • 講義資料、課題、クイズ、試験を整理して、1 か所にまとめる
  • 関連するトピックやモジュールごとに資料を分類する
  • 重要な概念、用語、数式をハイライトする
Organize and review course materials regularly
Regularly organizing and reviewing course materials will help you retain information more effectively and identify areas where you may need additional support.
Show steps
  • Set aside dedicated time for reviewing course materials
  • Create summaries or notes to reinforce your understanding
  • Identify any gaps in your knowledge and seek clarification
Identify a mentor who can provide guidance on Dataflow pipeline design and implementation
Finding a mentor who specializes in Dataflow can provide you with personalized guidance and support, accelerating your learning and helping you avoid common pitfalls.
Show steps
  • Network with professionals in the field of Dataflow
  • Attend industry events and conferences
  • Reach out to potential mentors and schedule introductory meetings
Five other activities
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Review Cloud Monitoring fundamentals
Brushing up on Cloud Monitoring fundamentals will help you understand how to monitor your Dataflow pipelines effectively.
Browse courses on Cloud Monitoring
Show steps
  • Review the Cloud Monitoring documentation
  • Set up a simple monitoring dashboard for a project
Google Cloud Platform のチュートリアルをフォローする
Google の専門家が作成したステップバイステップのガイドを介して、Dataflow の実用的な側面を学びます。
Browse courses on Dataflow
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  • 関連するチュートリアルを GCP のドキュメントから特定する
  • チュートリアルに記載されている手順を注意深く実行する
  • チュートリアルのコンセプトとコードを実践的なプロジェクトに適用する
練習問題を解く
Dataflow パイプラインを構築するための実践的な経験を提供します。
Browse courses on Dataflow
Show steps
  • Dataflow のドキュメントから練習問題を探す
  • 提供されているコードのサンプルを分析する
  • 独自の問題を考案し、解決する
ワークショップに参加する
業界の専門家から直接学び、Dataflow の詳細な側面について深く掘り下げることができます。
Browse courses on Dataflow
Show steps
  • Dataflow 関連のワークショップを見つける
  • ワークショップに登録して、参加する
  • 講師や参加者と積極的に交流し、質問する
Dataflow パイプラインを構築するプロジェクトに取り組む
現実的なパイプラインを構築することで、Dataflow の概念を適用し、運用上の課題を解決する能力をテストします。
Browse courses on Dataflow
Show steps
  • 現実的なビジネス要件に基づいてプロジェクトを定義する
  • 適切な Dataflow テクノロジーを選択する
  • パイプラインを設計、構築、テストする
  • パイプラインをデプロイして、結果を分析する

Career center

Learners who complete Serverless Data Processing with Dataflow: Operations - 日本語版 will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers use their knowledge of programming and big data tools to design, build, test, and maintain scalable data pipelines. This course may help a Data Engineer build a foundation in Dataflow operations, which is a crucial step in ensuring that data pipelines are efficient, reliable, and scalable. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Big Data Architect
Big Data Architects design and manage big data solutions that meet the needs of an organization. This course may help a Big Data Architect build a foundation in Dataflow operations, which is essential for designing and managing efficient, reliable, and scalable big data solutions. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Data Analyst
Data Analysts use their knowledge of data analysis and statistics to extract insights from data. This course may help a Data Analyst build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Data Scientist
Data Scientists use their knowledge of machine learning and statistics to build models that can predict future outcomes. This course may help a Data Scientist build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Software Engineer
Software Engineers design, develop, test, and maintain software systems. This course may help a Software Engineer build a foundation in Dataflow operations, which can be helpful for working on big data projects. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Cloud Architect
Cloud Architects design and manage cloud computing solutions that meet the needs of an organization. This course may help a Cloud Architect build a foundation in Dataflow operations, which is essential for designing and managing efficient, reliable, and scalable cloud solutions. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. This course may help a DevOps Engineer build a foundation in Dataflow operations, which can be helpful for working on big data projects. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Data Warehouse Manager
Data Warehouse Managers are responsible for managing and maintaining data warehouses. This course may help a Data Warehouse Manager build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course may help a Database Administrator build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Data Science Manager
Data Science Managers are responsible for managing and leading data science teams. This course may help a Data Science Manager build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. This course may help a Machine Learning Engineer build a foundation in Dataflow operations, which can be helpful for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Big Data Analyst
Big Data Analysts use their knowledge of big data tools and techniques to analyze large datasets. This course may help a Big Data Analyst build a foundation in Dataflow operations, which is essential for working with large datasets. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Data Architect
Data Architects design and manage data architectures that meet the needs of an organization. This course may help a Data Architect build a foundation in Dataflow operations, which is essential for designing and managing efficient, reliable, and scalable data architectures. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Product Manager
Product Managers are responsible for managing and developing products. This course may be helpful for a Product Manager who is working on a product that uses big data. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.
Business Analyst
Business Analysts use their knowledge of business and technology to analyze and solve business problems. This course may be helpful for a Business Analyst who is working on a project that uses big data. This course is especially helpful because it provides hands-on experience with Dataflow, which is one of the most popular big data processing tools on the market.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Serverless Data Processing with Dataflow: Operations - 日本語版 .
Provides an in-depth understanding of the architectural principles and design patterns for building data-intensive applications.
Serves as a comprehensive resource for Apache Spark, a unified analytics engine for large-scale data processing.

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