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Denys Shapovalov

Jest członkiem od 2022

Introduction to Data Engineering on Google Cloud Earned maj 4, 2025 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned kwi 6, 2025 EDT
Build Batch Data Pipelines on Google Cloud Earned mar 15, 2025 EDT
Tworzenie siatki danych przy użyciu Knowledge Catalog Earned lut 14, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned sty 19, 2025 EST
Implement Event-Driven Messaging and Automation Workflows Earned sty 12, 2025 EST

In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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Ukończ szkolenie wprowadzające Tworzenie siatki danych przy użyciu Knowledge Catalog, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: tworzenie siatki danych przy użyciu Knowledge Catalog w celu ułatwienia zarządzania danymi oraz ich wykrywania i ochrony w Google Cloud. Przećwiczysz i sprawdzisz swoje umiejętności w zakresie tagowania zasobów, przypisywania ról uprawnień i oceny jakości danych w Knowledge Catalog.

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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Earn a skill badge by completing the Implement Event-Driven Messaging and Automation Workflows skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.

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