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

Summary

Let's summarize this chapter. In this chapter, we covered three important topics in GCP—namely, IAM, project structure, and BigQuery ACLs. And as an addition, we've learned about the IaC practice.

Understanding these four topics lifts your knowledge from being a data engineer to becoming a cloud data architect. People with these skills can think not only about the data pipeline but also the higher-level architecture, which is a very important role in any organization.

Always remember the principle of least privilege, which is the foundation for architecting all the topics of IAM, project structure, and BigQuery ACLs. Always make sure only to give the right access to the right user.

In the next chapter, we will learn about costs. We want to understand how we should strategize costs in GCP. Strategizing doesn't only mean calculating the cost but also managing and optimizing it.