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Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud


Price: $18.49
(as of Dec 16,2024 02:46:35 UTC – Details)


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Packt is a leading publisher of technical learning content with the ability to publish books on emerging tech faster than any other.

Our mission is to increase the shared value of deep tech knowledge by helping tech pros put software to work.

We help the most interesting minds and ground-breaking creators on the planet distill and share the working knowledge of their peers.

ASIN ‏ : ‎ B0D11L956B
Publisher ‏ : ‎ Packt Publishing; 2nd edition (April 30, 2024)
Publication date ‏ : ‎ April 30, 2024
Language ‏ : ‎ English
File size ‏ : ‎ 32623 KB
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 797 pages


Data engineering is a crucial aspect of any data-driven organization, as it involves designing and building systems that collect, process, and analyze data to drive business insights. Google Cloud Platform offers a powerful set of tools and services that can help data engineers build scalable and efficient data platforms.

In this guide, we will explore how data engineers can level up their skills by leveraging Google Cloud Platform to build a scalable data platform. From data ingestion to processing and analysis, Google Cloud Platform provides a comprehensive suite of tools that can help data engineers streamline their workflows and unlock the full potential of their data.

Key topics covered in this guide include:

1. Data ingestion: Learn how to efficiently ingest data from various sources into Google Cloud Platform using tools like Cloud Storage, Cloud Pub/Sub, and Dataflow.

2. Data processing: Explore how to process and transform data at scale using tools like BigQuery, Dataflow, and Dataproc.

3. Data analysis: Discover how to build robust data pipelines for analytics and machine learning using tools like BigQuery ML, Data Studio, and AI Platform.

4. Monitoring and optimization: Learn how to monitor and optimize the performance of your data platform using tools like Stackdriver and Cloud Monitoring.

By following this guide, data engineers can gain a deeper understanding of how to leverage Google Cloud Platform to build a scalable and efficient data platform that can drive actionable insights for their organization. So, whether you are just starting out as a data engineer or looking to level up your skills, this guide will help you navigate the world of data engineering with Google Cloud Platform.
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