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

We've learned a lot of new things in this chapter about the cloud and GCP – let's summarize it. We started this chapter by accessing the GCP console for the first time. We then narrowed things down to find our first priority GCP services for data engineers to focus on.

And we closed the chapter by familiarizing ourselves with important features and terminologies such as quotas and service accounts. 

In the next chapter, we will do a lot more step-by-step, hands-on exercises with practical use cases using the services that we introduced in this chapter to build data solutions. So, make sure you've set up the GCP console properly and are ready for the exercises. In the next chapter, we will start by practicing developing a data warehouse. As we've learned in this chapter, the cloud data warehouse in GCP is BigQuery. We will start by learning about this very famous service – and one of the most important – for GCP data engineers...