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.
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Reading list
We've selected 40 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.
Authored by experts with Google Cloud backgrounds, this book is highly relevant to understanding the data governance aspects of platforms like Dataplex. It covers the essential components of a data governance program, including people, processes, and tools. strong reference for professionals and graduate students looking to operationalize data trustworthiness. It directly supports understanding how Dataplex fits into a broader data governance strategy.
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.
This recent book directly compares and contrasts various modern data architecture patterns, including concepts relevant to Dataplex such as data lakes and data mesh. It helps readers understand the strengths and weaknesses of each approach. It is highly valuable for professionals and graduate students trying to determine the best architectural fit for their needs and how platforms like Dataplex support these patterns. adds significant breadth by positioning Dataplex within the larger data architecture landscape.
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.
Provides practical guidance and examples for implementing the Data Mesh paradigm. It complements Zhamak Dehghani's foundational book by offering real-world insights and solutions. For those looking to apply Data Mesh principles using cloud platforms, this book offers valuable contemporary knowledge. It is most relevant for professionals and graduate students actively involved in designing and implementing modern data architectures.
Explores the principles and practices for managing data in large-scale environments. It covers various aspects of data management relevant to building and operating data platforms like Dataplex. The second edition includes updated content relevant to contemporary data challenges. It's a valuable resource for professionals and graduate students looking to deepen their understanding of scalable data management techniques.
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.
Offers a clear explanation of the data catalog concept and its role in enabling data discovery for analytics. It covers different types of data catalogs and their features. It's a good resource for gaining a broad understanding of data cataloging, which key feature of Dataplex. This book is suitable for undergraduate students and professionals new to the concept of data catalogs.
Presents a practical and less disruptive approach to implementing data governance within an organization. It focuses on integrating governance into existing processes, which is relevant when adopting a platform like Dataplex. It's a useful guide for professionals looking to implement data governance effectively without major organizational overhaul. This book provides a different perspective on data governance that complements the technical capabilities of platforms like Dataplex.
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.
Connects data governance with achieving data quality and delivering business value. It explores how effective governance practices contribute to trustworthy and valuable data assets. It complements the technical aspects of Dataplex by focusing on the organizational and business impact of data management. It is suitable for professionals and graduate students interested in the strategic aspects of data governance and quality.
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.
This foundational book delves into the critical role of metadata management in organizing and understanding data assets. Effective metadata management is essential for data catalogs and data governance, key features of Dataplex. While an older text, the core principles of metadata management remain highly relevant. It serves as a valuable reference for understanding the importance of metadata in a data platform context.
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.
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.
Considered a classic in the field of data quality, this book provides fundamental guidance on identifying, understanding, and addressing data quality issues. While older, the principles and techniques discussed remain highly relevant for anyone working with data, including on platforms like Dataplex. It's a foundational text for gaining a broad understanding of data quality concepts. is valuable as background reading to understand the historical context and core issues in data quality.
Offers a basic introduction to the concepts of data governance in an easy-to-understand format. It covers the fundamental principles and the value of implementing data governance. It is an excellent starting point for high school and undergraduate students, or anyone new to the topic, to gain a broad understanding of data governance as it relates to platforms like Dataplex. This book serves as helpful background reading.
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.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/e1stbs/dataple
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