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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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Table of Contents (19) Chapters Close

Preface 1. Part 1: Getting Started with Data Engineering with GCP FREE CHAPTER
2. Chapter 1: Fundamentals of Data Engineering 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

BigQuery’s useful features

Having completed the exercise from the previous section, where we used BigQuery in a practical scenario where we were developing a data warehouse, in this last section of the chapter, let’s bring back our perspective to see BigQuery as a tool.

BigQuery is an integral tool in the GCP data engineering ecosystem, so even though BigQuery at its core is a database, on top of that, there are many more features, such as ones for machine learning, transferring data, and scheduling queries.

I will use this section to guide you quickly through the important additional BigQuery features that you might use in the future. As usual, I will focus on helping you narrow down what is important to you as a data engineer.

As a reminder, the best source for detailed information about each feature is the GCP public documentation. This book will only give a high-level description of features so that you can understand when certain features are relevant to...

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