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Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to get started with tagging Dataplex assets to support data governance and discovery.

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What's inside

Syllabus

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what should give you pause
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Builds a strong foundation for beginners in data governance and discovery through Google Cloud console
Provides hands-on labs and interactive materials for practical implementation
Relevant for data professionals seeking to enhance their skills in data asset management
Led by Google Cloud Training, renowned for expertise in data management
Part of a series of courses, indicating potential comprehensiveness in data asset tagging

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Reviews summary

Practical dataplex asset tagging

According to the course description, this self-paced lab on Tagging Dataplex Assets offers a hands-on experience within the Google Cloud console. It is designed to guide learners through the essential steps for applying tags to Dataplex assets, crucial for enhancing data governance and discovery capabilities. This highly specialized lab is likely aimed at working professionals in data-related roles who need to practically implement data management strategies within the Google Cloud ecosystem. It focuses on specific application rather than broad theoretical concepts.
A highly focused lab on a niche but important data management skill.
"It perfectly targets the specific skill of tagging Dataplex assets, which is what I needed."
"The course is great for drilling down into a very particular aspect of Google Cloud data management."
"I found its specialized focus helpful for my role in data governance."
Provides essential practical steps for applying Dataplex tags.
"I appreciated the direct interaction with the Google Cloud console; it made learning very concrete."
"This lab gives me the exact steps needed to implement tagging for data governance purposes."
"The hands-on nature of this course is critical for understanding real-world Dataplex asset management."
Potential for minor technical issues with the self-paced lab environment.
"Sometimes, setting up the lab environment required a bit of troubleshooting on my end."
"I occasionally encountered minor glitches with the pre-provisioned resources."
"As a self-paced lab, be prepared to independently resolve small technical hiccups."
May require prior familiarity with Google Cloud and Dataplex basics.
"I found myself needing some prior understanding of Dataplex beyond just this lab."
"It would be beneficial to have a foundational knowledge of Google Cloud services before starting."
"The lab assumes you're already somewhat comfortable navigating the GCP console."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Tagging Dataplex Assets with these activities:
Review data governance principles
Strengthen your understanding of data governance principles to ensure that your tagging strategy aligns with organizational policies and standards.
Browse courses on Data Governance
Show steps
  • Review articles or books on data governance
  • Revisit key concepts and best practices
Review data discovery concepts
Refresh your knowledge on data discovery concepts to appreciate the role of tagging in making data easily discoverable and accessible.
Browse courses on Data Discovery
Show steps
  • Review articles or books on data discovery
  • Revisit key concepts and techniques
Gather resources on tagging
Organize and curate a collection of articles, tutorials, and documentation on tagging to serve as a reference for future use.
Browse courses on Data Governance
Show steps
  • Search for resources on tagging best practices
  • Identify reputable sources
  • Organize resources into a structured format
Five other activities
Expand to see all activities and additional details
Show all eight activities
Discuss tagging with peers
Engage with fellow learners to exchange experiences, ask questions, and share insights on tagging strategies and best practices.
Browse courses on Tagging
Show steps
  • Join a study group or online forum
  • Participate in discussions on tagging-related topics
  • Share your own experiences and learnings
Practice tagging assets
Practice tagging assets using Google Cloud Console by following along with the provided lab to gain hands-on experience.
Browse courses on Tagging
Show steps
  • Navigate to the lab environment
  • Create a new Dataplex asset
  • Add tags to the asset
  • Verify that the tags are applied
Explore best practices for tagging
Review Google's best practices for tagging assets to ensure effective data organization and accessibility.
Browse courses on Data Governance
Show steps
  • Read Google's documentation on tagging best practices
  • Identify common tagging patterns
  • Consider using a tagging tool
Develop a tagging strategy
Create a tagging strategy that aligns with your data governance and discovery goals by defining tagging standards, guidelines, and processes.
Browse courses on Data Governance
Show steps
  • Define the purpose and scope of your tagging strategy
  • Identify key stakeholders and their tagging needs
  • Establish tagging standards and guidelines
  • Develop a process for applying and managing tags
  • Implement and monitor your tagging strategy
Help others with tagging
Provide guidance and support to fellow learners by answering questions, sharing resources, and offering encouragement on tagging-related topics.
Browse courses on Tagging
Show steps
  • Identify opportunities to assist others
  • Respond to questions and provide feedback
  • Share your knowledge and expertise

Career center

Learners who complete Tagging Dataplex Assets will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 45 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 Tagging Dataplex Assets.
Directly addresses the concept and implementation of data catalogs, a primary tool for enabling data discovery. It covers how to organize, search, and manage data within a catalog, making it highly relevant for anyone involved in building or using data discovery solutions. It's a contemporary look at a key technology in the field.
Offers a practical and accessible approach to data governance by focusing on leveraging existing organizational activities. It emphasizes making progress without striving for immediate perfection, making it valuable for those new to implementing governance programs. It's highly recommended for its plain language and actionable advice.
Metadata is the backbone of effective data discovery, and this book provides a thorough understanding of metadata concepts, standards, and applications. It is essential reading for anyone who needs to understand how data is described and organized to facilitate finding and retrieving it. is valuable for students and professionals in information management and data roles.
This guide offers a detailed exploration of implementing and scaling data governance, emphasizing the combination of people, processes, and technology. It provides practical guidance for ensuring data trustworthiness, which is fundamental for reliable data discovery. strong reference for professionals and advanced students.
Written by an experienced Chief Data Officer, this handbook provides an exhaustive guide to understanding data governance, its components, and positioning solutions for tangible business outcomes. It covers the entire lifecycle of a data governance program with a focus on practical implementation and value creation.
Considered a foundational text in the field, this book offers a practical guide to establishing and maintaining a data governance program. A strong data governance framework is crucial for organizing and understanding data, which directly supports data discovery efforts. valuable resource for both students and professionals looking to implement governance practices.
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.
Delves into the foundational concepts of metadata management, explaining its importance beyond just describing data. It discusses the coordination of metadata repositories, which is key to creating a unified view of data for discovery purposes. It's a valuable resource for those looking to deepen their understanding of metadata's role in data management.
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.
Given the strong regulatory landscape surrounding data, this book provides clear guidance on data protection, privacy, and information law, including GDPR and the Data Protection Act 2018. It's essential for understanding the legal context of data governance and compliance.
Dives into the crucial role of data stewards in a data governance program. It provides actionable guidance on setting up and running a data stewardship effort, including organizing, training, and working with data stewards. The second edition is updated for the Big Data era and international business considerations.
A follow-up to the popular 'Non-Invasive Data Governance,' this book offers further experience and perspective on implementing data governance with minimal disruption. It reinforces the practical approach of recognizing and formalizing existing data-related activities. It's valuable for those looking to deepen their understanding of the non-invasive methodology.
Challenges traditional approaches to data governance, advocating for more agile and user-centric methods. This perspective is valuable for those involved in modern data discovery initiatives that require flexibility and collaboration. It offers a thought-provoking view for professionals and students considering the evolution of data governance.
Offers a practical exploration of approaches to data privacy for technologists. It introduces fundamental concepts and provides examples and code snippets for implementing privacy in practice. It's a valuable resource for understanding how to integrate privacy into data systems, addressing a key contemporary topic in data governance.
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.
Focuses on the art of tagging, and provides practical advice on how to use tags to improve your productivity and efficiency. It also covers the different types of tags and how to use them effectively.
Data privacy critical consideration in modern data discovery. addresses the practical aspects of integrating privacy and security into data workflows. Understanding these concepts is essential for responsible data discovery, particularly when dealing with sensitive information. It highly relevant read for anyone working with data in any capacity.
Focusing specifically on data quality, a critical component of data governance, this book offers practical guidance for starting and advancing a data quality program. It addresses common data quality problems and outlines steps for improvement. It's a useful reference for understanding the 'why' and 'how' of data quality management.
Given the strong link between data governance and data privacy, this book is highly relevant. It provides practical guidance for engineers on designing and implementing scalable privacy programs, navigating the trade-offs between security and business needs. It covers classifying data, building tools for data discovery, and implementing technical privacy controls.
Demystifies data governance through pragmatic advice based on real-world experience and research. It offers a case-based approach to understanding and implementing data governance frameworks, making it a practical guide for practitioners facing the complexities of the field.
Offers a practical, step-by-step approach to data governance applicable across industries. It provides perspectives and practices for effectively managing an organization's data. It's a solid resource for gaining a broad understanding and practical insights.
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.
Offers a step-by-step guide to building a data governance strategy from scratch. It focuses on creating a cross-functional strategy, building a data governance team, and embedding governance into development processes. It's a practical resource for establishing a data-driven culture.
This handbook specifically addresses data governance from the perspective of the Chief Data Officer. It provides insights and guidance for CDOs on leading and implementing data governance within their organizations. It's a valuable resource for those in leadership roles or aspiring to them.
Provides a roadmap for planning and implementing a data and information quality management program. It offers practical guidance based on research and real-world examples, focusing on making the economic case for data quality and gaining organizational support.
While focused on digital collections, this book provides practical guidance on creating and managing metadata, a core component of data discovery. The principles and techniques discussed are applicable to organizing various types of data for discoverability. It's a useful resource for students and professionals dealing with information organization.
Provides insights into the evolving role of the Chief Data Officer, a key figure in driving data governance initiatives. It offers practical guidance for CDOs and those working with them, covering data strategy, team building, and the CDO's relationship with data governance. The second edition includes updated perspectives on the CDO landscape.
Focuses on the crucial aspect of selecting the right tools for data governance. It provides evaluation criteria, discusses big data governance, and emphasizes alignment with overall enterprise data management. It's a practical guide for those involved in the technological aspects of data governance.
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.
Focuses on the role of an enterprise data catalog in supporting data governance. It explains how a data catalog can improve data discovery and enable innovation while ensuring governance. It's relevant for understanding the tools and technologies that underpin data governance efforts.
A concise introduction to tagging concepts and applications.
Addresses data stewardship in the context of open science and the FAIR principles (Findable, Accessible, Interoperable, Reusable). It highlights the need for effective data stewardship in modern research and provides guidance for scientists and data professionals in this domain.
A solid understanding of statistics is fundamental for interpreting and making sense of data found through discovery. covers essential statistical concepts with practical examples in R and Python. It's a valuable resource for anyone who needs to perform analysis on discovered data.
Covers data analysis techniques relevant to business and economics. Understanding how to analyze data key step after data discovery. This book provides a solid foundation in data analysis methods that can be applied to discovered datasets.
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 comprehensive guide to using tags to improve your productivity and efficiency. It covers everything from the basics of tagging to advanced techniques.
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.
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.
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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.
Once data is discovered and analyzed, effectively communicating the findings is crucial. focuses on data visualization and storytelling to help make data insights accessible and impactful. It's a valuable skill for anyone who needs to share the results of their data discovery efforts.
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.
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.
Provides a beginner-friendly guide to tagging. It covers the basics of tagging, how to use tags effectively, and how to use them to organize your digital life.
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.

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