「Google Cloud の ML API 用にデータを準備」コースの入門スキルバッジを獲得できるアクティビティを修了すると、 Dataprep by Trifacta を使用したデータのクリーニング、Dataflow でのデータ パイプラインの実行、Dataproc でのクラスタの作成と Apache Spark ジョブの実行、 Cloud Natural Language API、Google Cloud Speech-to-Text API、Video Intelligence API などの ML API の呼び出しに関するスキルを証明できます。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジで、 インタラクティブなハンズオン環境での知識の応用力を証明するものです。このスキルバッジ コースと最終評価チャレンジラボを修了し、 スキルバッジを獲得してネットワークで共有しましょう。
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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This course explores the Geographic Information Systems (GIS), GIS Visualization, and machine learning enhancements to BigQuery.
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This course explores how to implement a streaming analytics solution using Dataflow and BigQuery.
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This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.
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This course explores how to implement a streaming analytics solution using Pub/Sub.
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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataflow.
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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Cloud Data Fusion.
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This course explores the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.
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This course identifies best practices for migrating data warehouses to BigQuery and the key skills required to perform successful migration.
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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.
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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.
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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
BigQuery ML を使用した予測モデリング向けのデータ エンジニアリング
Earned 1月 8, 2025 EST
BigQuery でデータ ウェアハウスを構築する
Earned 1月 8, 2025 EST
Google Cloud の ML API 用にデータを準備
Earned 1月 7, 2025 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned 5月 23, 2024 EDT
Data Warehousing for Partners: BigQuery Extended Capabilities
Earned 3月 19, 2024 EDT
Data Warehousing for Partners: Streaming Analytics
Earned 3月 17, 2024 EDT
Data Warehousing for Partners: Analyze Data with Looker
Earned 3月 17, 2024 EDT
Data Warehousing for Partners: Stream Data with Pub/Sub
Earned 3月 17, 2024 EDT
Data Warehousing for Partners: Process Data with Dataflow
Earned 3月 16, 2024 EDT
Data Warehousing for Partners: Cloud Data Fusion Pipelines
Earned 3月 11, 2024 EDT
Data Warehousing for Partners: Process Data with Dataproc
Earned 3月 11, 2024 EDT
Data Warehousing for Partners: Migrate Data to BigQuery
Earned 3月 5, 2024 EST
Data Warehousing for Partners: Optimize in BigQuery
Earned 1月 31, 2024 EST
Data Warehousing for Partners: Design in BigQuery
Earned 1月 30, 2024 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned 1月 15, 2024 EST