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Data Engineering with Google Cloud Platform

You're reading from   Data Engineering with Google Cloud Platform A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781835080115
Length 476 pages
Edition 2nd Edition
Languages
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Author (1):
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Adi Wijaya Adi Wijaya
Author Profile Icon Adi Wijaya
Adi Wijaya
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1: Getting Started with Data Engineering with GCP
2. Chapter 1: Fundamentals of Data Engineering FREE CHAPTER 3. Chapter 2: Big Data Capabilities on GCP 4. Part 2: Build Solutions with GCP Components
5. Chapter 3: Building a Data Warehouse in BigQuery 6. Chapter 4: Building Workflows for Batch Data Loading Using Cloud Composer 7. Chapter 5: Building a Data Lake Using Dataproc 8. Chapter 6: Processing Streaming Data with Pub/Sub and Dataflow 9. Chapter 7: Visualizing Data to Make Data-Driven Decisions with Looker Studio 10. Chapter 8: Building Machine Learning Solutions on GCP 11. Part 3: Key Strategies for Architecting Top-Notch Solutions
12. Chapter 9: User and Project Management in GCP 13. Chapter 10: Data Governance in GCP 14. Chapter 11: Cost Strategy in GCP 15. Chapter 12: CI/CD on GCP for Data Engineers 16. Chapter 13: Boosting Your Confidence as a Data Engineer 17. Index 18. Other Books You May Enjoy

Building Workflows for Batch Data Loading Using Cloud Composer

In data engineering, the definition of a workflow is a set of configurations to automate tasks, jobs, and their dependencies. If we are talking about database workflow, we talk about how to automate the table creation process.

The main objects in any database system are tables, and one of the main differences between an application database and a data warehouse is the creation of tables. Compared to tables in application databases, where tables are mostly static and created to support frontend applications, tables in data warehouses are dynamic. The table is the main product as it is a collection of business logic, and data flows.

In this chapter, we will learn how to create the workflow for our data warehouse tables from Chapter 3, Building a Data Warehouse in BigQuery. We will learn how to automate the table creations using a Google Cloud Platform (GCP) service called Cloud Composer. This will include how to create...

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