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Data Engineering with Google Cloud Platform

You're reading from   Data Engineering with Google Cloud Platform A practical guide to operationalizing scalable data analytics systems on GCP

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781800561328
Length 440 pages
Edition 1st 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 (17) Chapters Close

Preface 1. Section 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. Section 2: Building Solutions with GCP Components
5. Chapter 3: Building a Data Warehouse in BigQuery 6. Chapter 4: Building Orchestration 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 for Making Data-Driven Decisions with Data Studio 10. Chapter 8: Building Machine Learning Solutions on Google Cloud Platform 11. Section 3: Key Strategies for Architecting Top-Notch Data Pipelines
12. Chapter 9: User and Project Management in GCP 13. Chapter 10: Cost Strategy in GCP 14. Chapter 11: CI/CD on Google Cloud Platform for Data Engineers 15. Chapter 12: Boosting Your Confidence as a Data Engineer 16. Other Books You May Enjoy

Understanding how Data Studio can impact the cost of BigQuery

At a very high level, the total BigQuery cost is driven by how big your data is and the amount of usage. Both factors work as multipliers. For example, if you have a table that's 1 TB in size and you access the table 10,000 times in a month, it means the BigQuery cost will be 1 TB x 10,000 x $5 = $50,000 / month.

Whether $50,000 is expensive or not depends on your organization. But we will ignore the context and focus on the cost driver aspects, so let's say $50,000 is expensive. Now the questions are what kind of table could be 1 TB in size? and how can a table be accessed 10,000 times in a month? Let's discuss these questions in the following sections.

What kind of table could be 1 TB in size?

To answer that, let's take a look at our data warehouse diagram from Chapter 3, Building a Data Warehouse in BigQuery, in the following figure:

Figure 7.25 – High-level data...

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