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Sada Shiva Kumar Reddy Suluguri

Учасник із 2024

Діамантова ліга

Кількість балів: 11415
Building Resilient Streaming Systems on Google Cloud Platform Earned лип. 31, 2024 EDT
Build Batch Data Pipelines on Google Cloud Earned лип. 19, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned лип. 8, 2024 EDT
Get Started with Dataplex Earned черв. 26, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals - українська Earned черв. 25, 2024 EDT
Preparing for your Professional Data Engineer Journey Earned черв. 23, 2024 EDT

This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn to build streaming data pipelines using Google cloud Pub/Sub and Dataflow to enable real-time decision making. You will also learn how to build dashboards to render tailored output for various stakeholder audiences.

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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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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.

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Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.

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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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