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Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform

By : Adi Wijaya
4.7 (12)
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Data Engineering with Google Cloud Platform

Data Engineering with Google Cloud Platform

4.7 (12)
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)
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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

Unlocking the power of your data with Data Studio

Data Studio is a tool for you to visualize your data fully on the cloud. There are two main reasons why we need data visualization; the first is exploration and the second is reporting: 

  • Data visualization for exploration

As a data engineer, even though visualizing data is not your main responsibility, there are times when visualizing data may help in your job. For example, at times when you need to optimize your data pipeline, you may need to analyze a job's performance. Visualizing the job's data will help you get more information. If you have a data science background, you may be familiar with tools such as Jupyter Notebook. It is a fully fledged tool for data analytics, including visualization for exploration. But in our case, we may only need to quickly visualize a bar chart from a BigQuery table, for example. And in that case, Data Studio is the best option due to its simplicity and seamless connectivity...

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