Book Image

Data Engineering with Google Cloud Platform

By : Adi Wijaya
3 (1)
Book Image

Data Engineering with Google Cloud Platform

3 (1)
By: Adi Wijaya

Overview of this book

With this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.
Table of Contents (17 chapters)
1
Section 1: Getting Started with Data Engineering with GCP
4
Section 2: Building Solutions with GCP Components
11
Section 3: Key Strategies for Architecting Top-Notch Data Pipelines

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 ID, and author ID
  • An author portal application using MySQL Database to store authors' personal information, including age

Do the following:

  1. List important follow-up questions for your manager.
  2. List 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 at each step, and finally, how you want to serve the information to end users.