August 13, 2024
Updated July 22, 2025
14 minute read
A Comprehensive Guide to Google Cloud Dataplex
In the world of data, organizations often find themselves with vast and valuable information scattered across different systems, from data lakes to data warehouses and beyond. Managing this distributed data, ensuring its quality, and governing its use can be a monumental challenge. This is where Google Cloud Dataplex steps in. At a high level, Dataplex is an intelligent data fabric that allows organizations to centrally manage, monitor, and govern their data across these disparate sources without having to move it. It provides a single, unified interface to organize, secure, and analyze data at scale.
e1stbs|
Find a path to becoming a Dataplex. Learn more at:
OpenCourser.com/topic/e1stbs/dataple
Reading list
We've selected 18 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Dataplex.
This study guide is specifically designed for the Google Cloud Professional Data Engineer certification, which covers many services relevant to Dataplex, including data lakes, data processing, and governance on GCP. It's an excellent resource for understanding how Dataplex fits within the broader Google Cloud data ecosystem and preparing for practical application.
Addressing the critical issue of data quality in modern data pipelines, this book offers practical strategies for ensuring data trustworthiness. It covers concepts relevant to Dataplex's data quality features and valuable resource for data engineers and practitioners focused on building reliable data assets within a data lake or similar environment.
Delves into the concepts, technology, and practice of enterprise data catalogs. It explains how data catalogs enable data discovery, support data governance, and foster innovation. Given Dataplex's strong data cataloging capabilities, this book provides essential background and in-depth knowledge for leveraging such features effectively.
While not specific to Dataplex, this book foundational text for understanding the underlying principles of data systems, including storage, processing, and consistency. It provides essential background knowledge for anyone working with large-scale data platforms in the cloud, offering insights into the trade-offs and designs behind systems like those underpinning Dataplex.
Challenges traditional approaches to data governance and advocates for a more agile and people-centric model. It offers a contemporary perspective on governance that aligns well with the distributed and flexible nature of cloud-based data platforms and data meshes, providing insights relevant to governing data in a Dataplex environment.
Provides a practical framework for incorporating ethical principles into data management and governance. As organizations handle increasing amounts of data, understanding data ethics is crucial. This book is highly relevant for ensuring responsible data handling within Dataplex and related data initiatives.
As a comprehensive reference for data management principles and practices, the DMBOK provides a broad understanding of various data management functions, including data governance, data quality, and metadata management. It's a foundational text for anyone serious about data management and provides a vendor-neutral perspective relevant to Dataplex's capabilities.
A foundational book on data governance, this resource provides practical guidance on establishing and maintaining a data governance program. It covers essential aspects like policies, processes, and organizational roles. Understanding these concepts is crucial for effectively governing data within a platform like Dataplex.
Takes a deeper, more critical look at data ethics, focusing on the power dynamics inherent in data processing and AI. It's relevant for advanced students and professionals who want to understand the broader societal impact and ethical challenges associated with large-scale data platforms like those managed with Dataplex.
Focusing on the practical aspects of data stewardship, this book provides actionable guidance for managing and governing data effectively. It valuable resource for understanding the roles and responsibilities involved in data governance, which is directly applicable to managing data assets within Dataplex.
A more accessible introduction to streaming systems compared to Akidau's book, this resource explains core concepts in a reader-friendly manner. It's suitable for those new to real-time data processing and provides helpful background for understanding data pipelines that might feed into or interact with Dataplex.
Provides a detailed framework and techniques for assessing data quality. Understanding data quality dimensions and assessment methods is essential for ensuring reliable data in any data platform, including Dataplex. It serves as a strong reference for data quality professionals.
Foundational text on the concepts and practices of large-scale data processing, particularly streaming data. While not directly about Dataplex, understanding streaming systems is relevant for ingesting real-time data into a data lake, a common use case for Dataplex.
One of the earlier books to focus on data ethics, this resource explores the ethical implications of big data and the potential for data ethics to be a competitive advantage. It provides a broader societal context for the importance of ethical data handling within platforms like Dataplex.
This edited collection explores various aspects of managing and analyzing big data in cloud environments. It covers a range of research and applications, providing insights into the challenges and advancements in cloud-based big data, which is directly relevant to the use cases for Dataplex.
Offers a practical, step-by-step guide to planning and executing data quality projects. It provides valuable methodologies and best practices that can be applied when working with data in Dataplex to improve its quality and trustworthiness.
Providing a general overview of big data management and analytics, this book covers fundamental concepts and ecosystems. It can serve as introductory reading for those new to the big data space, offering context for the challenges that platforms like Dataplex are designed to address.
Focuses on developing and managing databases in a cloud environment. While databases are distinct from data lakes, the principles of cloud-based data management and deployment discussed are relevant background for understanding cloud data platforms like Dataplex.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/e1stbs/dataple
Save
