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Data Engineering with Google Cloud Platform - Second Edition

You're reading from  Data Engineering with Google Cloud Platform - Second Edition

Product type Book
Published in Apr 2024
Publisher Packt
ISBN-13 9781835080115
Pages 476 pages
Edition 2nd Edition
Languages
Author (1):
Adi Wijaya Adi Wijaya
Profile icon Adi Wijaya

Table of Contents (19) Chapters

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

The past, present, and future of data engineering

The data engineering practice has been there since the early internet era in the 1990s. Going back to Chapter 1, Fundamentals of Data Engineering, in the Start with knowing the roles of a data engineer section, in the past, data engineers were mostly ETL developers using specific tools. Most of these tools were proprietary tools and located on-premises. The term data engineer itself wasn’t commonplace; the more common terms used to be data modelers, database admin, and ETL developer (ETL references the proprietary ETL tool’s name). Each of the ETL tools had the necessary expertise and best practices surrounding them.

Now, in the present, data engineering has evolved into a more mature and singular role. This means that the practice is receiving a lot more common principles, concepts, and best practices. This is due to two reasons – the rapid improvement in the technologies supporting the practice and the fact...

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