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

A quick overview of GCP services for data engineering

As you can see in the GCP Console navigation bar, there are a lot of services in GCP. The services are not only limited to data and analytics. They also cover other areas such as application development, machine learning, networks, source repositories, and many more. As a data engineer working on GCP, you will face situations when you need to decide which services you need to use for your organization.

You might be wondering, who in an organization should decide on the services to use? Is it the CTO, IT manager, solution architect, or data engineers? The answer depends on the experience of using GCP of each of them. But most of the time, data engineers need to be involved in the decision.

So how should we decide? In my experience, there are three important decision factors:

  • Choose services that are serverless.
  • Understand the mapping between the service and the data engineering areas.
  • If there is more than...