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

Chapter 2: Big Data Capabilities on GCP

One of the most common scenarios when people start using Google Cloud Platform or GCP is getting lost because there are too many products and services. GCP offers a very broad range of services for multiple disciplines, for example, for application development, microservices, security, AI, and of course, one of them is Big Data. But even for big data products, there are multiple options that you can choose. 

As an analogy, GCP is like a supermarket. A supermarket has almost everything that you need to support your daily life. For example, if you plan to cook pasta and go to a supermarket to buy the ingredients, no one will tell you what ingredients you should buy, or even if you know the ingredients, you will still be offered the ingredients by different brands, price tags, and producers. If you fail to make the right decision, you will end up cooking bad pasta. In GCP it's the same; you need to be able to choose your own services...