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Samuel Warman

Учасник із 2021

Бронзова ліга

Кількість балів: 3560
Getting Started with Terraform for Google Cloud Earned січ. 21, 2024 EST
Build Streaming Data Pipelines on Google Cloud Earned груд. 3, 2023 EST
Build Batch Data Pipelines on Google Cloud Earned трав. 20, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned квіт. 30, 2023 EDT
Achieving Advanced Insights with BigQuery - Locales Earned лют. 17, 2023 EST
Creating New BigQuery Datasets and Visualizing Insights Earned лют. 5, 2023 EST
Exploring and Preparing your Data with BigQuery Earned лют. 3, 2023 EST
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська Earned січ. 27, 2023 EST
Create and Manage Cloud Resources Earned січ. 21, 2023 EST

This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.

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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.

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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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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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This course, Achieving Advanced Insights with BigQuery - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Achieving Advanced Insights with BigQuery. The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.

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Пройдіть квест Create and Manage Cloud Resources й отримайте skill badge. Ви навчитеся виконувати наведені нижче дії. Писати команди gcloud і використовувати Cloud Shell, створювати й розгортати віртуальні машини в Compute Engine, запускати контейнерні додатки за допомогою Google Kubernetes Engine, а також налаштовувати розподілювачі навантаження для мережі й HTTP.Skill badge – це ексклюзивна цифрова винагорода, яка підтверджує, що ви вмієте працювати з продуктами й сервісами Google Cloud, а також застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати skill badge й показати його колегам, пройдіть цей квест і підсумковий тест.

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