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Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform - Second Edition

By : Adi Wijaya
4.5 (6)
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Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform

4.5 (6)
By: Adi Wijaya

Overview of this book

The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.
Table of Contents (19 chapters)
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1
Part 1: Getting Started with Data Engineering with GCP
4
Part 2: Build Solutions with GCP Components
11
Part 3: Key Strategies for Architecting Top-Notch Solutions

Exercise

You are a data engineer at a book publishing company and your product manager has asked you to build a dashboard to show the total revenue and customer satisfaction index in a single dashboard.

Your company doesn’t have any data infrastructure yet, but you know that your company has these three applications that contain TBs of data:

  • The company website
  • A book sales application using MongoDB to store sales transactions, including transactions, book IDs, and author IDs
  • An author portal application using a MySQL Database to store authors’ personal information, including age

Do the following:

  1. List down important follow-up questions for your manager
  2. List down your technical thinking process of how to do it at a high level
  3. Draw a data pipeline architecture

There is no right or wrong answer to this practice. The important thing is that you can imagine how the data flows from upstream to downstream, how it should be processed...

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Data Engineering with Google Cloud Platform
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