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

Understanding CI/CD components with GCP services

There are some steps in the CI/CD practice. Each step may involve different tools or GCP services. To understand this concept better, let's take a look at the following diagram:

Figure 11.1 – The CI/CD steps and the GCP services involved

The diagram shows the high-level steps of a complete CI/CD. At each step, there is a corresponding GCP service that can handle that step. For example, the first step is Source Code. In GCP, you can create a GitHub repository using a service called Cloud Source Repository. Later, in the Exercise – implementing continuous integration using Cloud Build section, we will learn how to create one. For now, let's understand the steps and what GCP services are involved:

  1. The CI process starts from Source Code. This Source Code should always be managed in a GitHub repository. It can be in GitHub, GitLab, or any other Git provider. As we mentioned previously...