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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 Dataplex using the command line by walking you through creating a lake, adding a zone, attaching and detaching assets, and deleting zones and lakes.

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What's inside

Syllabus

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Taught by Google Cloud Training, who develops widely used Google Cloud products and services
Suitable for beginners who wish to gain foundational knowledge in Dataplex
Provides hands-on labs for practical application of concepts
Focuses on command-line operations, appealing to learners with technical backgrounds
Covers core Dataplex operations like creating lakes, adding zones, and attaching assets
Suited for individuals seeking an introduction to Dataplex for data management and analysis

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Reviews summary

Quick command-line dataplex start

According to students, this course provides a quick and practical introduction to Google Cloud Dataplex, primarily focusing on command-line operations. Learners find the hands-on lab format highly effective for understanding core concepts like creating lakes and managing zones. While it's lauded for being a great starting point and clarifying fundamental tasks, some caution that it offers a 'qwik start' level of depth, meaning it doesn't delve into advanced topics or complex scenarios. It's best suited for those seeking a rapid grasp of Dataplex CLI essentials.
Strictly focuses on CLI, which is both a strength and a limitation.
"If you're looking for GUI interactions, this isn't it; it's purely command-line driven."
"I needed to learn Dataplex via CLI, and this course directly addressed that need."
"The command-line focus is great for automation scripts but less intuitive for visual learners."
Delivers a rapid overview of Dataplex fundamentals for beginners.
"This course is ideal for a quick introduction to Dataplex and its core functionalities."
"It helped me get started very quickly, covering the basics without overwhelming detail."
"Perfect for understanding the initial setup and basic management of Dataplex via command line."
Excellent for direct application of Dataplex command-line tasks.
"The lab environment works well and provides a direct way to practice Dataplex commands."
"I appreciated the step-by-step instructions that allowed me to get hands-on with the Dataplex CLI."
"Executing commands directly in the Google Cloud console made the learning very concrete."
Some reported commands or lab steps might not align with current GCP updates.
"Occasionally encountered issues where lab instructions seemed slightly out of sync with the current GCP console."
"Had to do some troubleshooting as a few commands had changed since the lab was published."
"It would be beneficial if the lab were regularly updated to reflect the latest Dataplex CLI."
Provides basics, but lacks advanced topics or deeper conceptual explanations.
"The content is quite basic and doesn't cover complex use cases or best practices."
"Good for a first glance, but I wish there was more explanation on the 'why' behind the commands."
"Don't expect to become a Dataplex expert; it's purely a rapid intro to the command line."

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 Dataplex: Qwik Start - Command Line with these activities:
Lakes, Zones, and Assets
This project will help you build hands-on experience using Dataplex lakes, zones, and assets.
Browse courses on Dataplex
Show steps
  • Create a Dataplex lake and add a zone
  • Attach a bigquery dataset to the lake
  • Create a Dataplex zone in the lake
  • Detach the bigquery dataset from the lake
  • Delete the Dataplex zone and lake
Use command line commands to create a lake
Deepens understanding of how to create lakes and Zones in Dataplex using the command line, which is a common way to create lakes in a real-world coding environment.
Show steps
  • Open a terminal window and navigate to the folder where you want to create the lake.
  • Create a new lake using the `gcloud dataplex lakes create` command.
  • Specify the name, location, and other options for the lake.
Practice attaching and detaching assets to a Zone
Provides hands-on experience in attaching and detaching assets to Zones, reinforcing understanding of data organization and access control.
Browse courses on Assets
Show steps
  • Create a new Zone in a lake.
  • Attach an existing asset to the Zone.
  • Detach the asset from the Zone.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Dataplex Concepts
These exercises will help you solidify your understanding of key Dataplex concepts like lakes, zones, and assets.
Browse courses on Dataplex
Show steps
  • Define a Dataplex lake
  • Define a Dataplex zone
  • Define a Dataplex asset
Follow a tutorial on using Dataplex Zones
Enhances understanding of how to use Zones to partition data in a lake, ensuring efficient data management and improved query performance.
Browse courses on Zones
Show steps
  • Find a tutorial on using Dataplex Zones.
  • Follow the steps in the tutorial to create a new Zone.
  • Attach the Zone to an existing lake.
Practice deleting Zones and lakes
Reinforces understanding of how to manage and clean up Dataplex resources by providing hands-on practice in deleting Zones and lakes.
Browse courses on Zones
Show steps
  • Create a new Zone and lake.
  • Delete the Zone.
  • Delete the lake.
Create a diagram of a Dataplex lake architecture
Reinforces understanding of the components and relationships within a Dataplex lake architecture, solidifying knowledge of data organization and management.
Show steps
  • Research the different components of a Dataplex lake architecture.
  • Draw a diagram that shows the relationships between these components.
  • Label the different components and explain their functions.
Write a summary of the benefits of using Dataplex
Enhances understanding of the advantages and value proposition of Dataplex, encouraging students to reflect on its impact on data management and analytics.
Show steps
  • Research the benefits of using Dataplex.
  • Write a summary that highlights the key benefits.
  • Include examples of how Dataplex can be used to solve real-world data challenges.
Contribute to the Dataplex documentation
Extends understanding of Dataplex beyond the course material, encourages engagement with the broader community, and fosters a deeper understanding of the technology's capabilities.
Show steps
  • Find an area in the Dataplex documentation that you would like to improve.
  • Make a change to the documentation and submit a pull request.
  • Work with the Dataplex team to get your changes merged.

Career center

Learners who complete Dataplex: Qwik Start - Command Line will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 42 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: Qwik Start - Command Line.
Classic guide to the Unix operating system and its command-line tools. It covers everything from basic commands to advanced topics like shell scripting and system administration.
Provides a roadmap for the future of data connectivity. It discusses the latest trends and technologies that are driving the evolution of data connectivity, and it outlines the challenges and opportunities that lie ahead. This book must-read for anyone who wants to stay ahead of the curve in this rapidly changing field.
Comprehensive guide to the Bash command-line shell. It covers everything from basic commands to advanced topics like shell scripting and system administration. The author, Cameron Newham, highly respected expert in the field of Unix and Linux.
Provides a roadmap for the future of data connectivity. It discusses the latest trends and technologies that are driving the evolution of data connectivity, and it outlines the challenges and opportunities that lie ahead. This book must-read for anyone who wants to stay ahead of the curve in this rapidly changing field.
Focuses on the Data Lakehouse, a contemporary architectural pattern that combines the benefits of Data Lakes and Data Warehouses. Authored by a pioneer in the field, it provides insights into building and leveraging this modern approach to data management and analytics. This key resource for understanding current developments.
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.
While not exclusively about Data Lakes, this book foundational text for anyone working with large-scale data systems. It delves into the fundamental concepts of data storage, processing, and transmission, which are crucial for understanding the underlying principles of Data Lake architecture and design. It's highly valuable for deepening your understanding of the technical challenges and trade-offs involved.
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.
Focuses on the practical implementation of the Data Lakehouse architecture. It covers design considerations, challenges, and best practices, providing a hands-on perspective on building a modern data platform that leverages Data Lakes. This valuable resource for those looking to implement a Data Lakehouse.
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.
This guide provides a concise yet comprehensive explanation of adopting a Data Lakehouse architecture. It reviews design considerations, challenges, and best practices, offering key insights into managing structured and unstructured data and supporting various use cases. This practical resource for understanding and implementing the Data Lakehouse.
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.
Helps navigate the complex landscape of modern data architectures, including Data Lakes and the emerging Data Lakehouse concept. It provides a comparative analysis of different approaches, aiding in understanding where Data Lakes fit within the broader data ecosystem and informing decisions about the most suitable architecture for specific needs. This is particularly useful for understanding contemporary trends.
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.
Apache Spark powerful processing engine often used with Data Lakes. This book, written by the creators of Spark, provides a comprehensive guide to using, deploying, and maintaining Spark. It's essential for anyone who will be processing data within a Data Lake environment, offering deep insights into Spark's capabilities and optimization.
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.
Data governance critical aspect of managing Data Lakes effectively and preventing them from becoming 'data swamps.' provides a comprehensive guide to establishing data governance programs, covering the necessary people, processes, and tools. It's essential for ensuring the quality, security, and usability of data within a Data Lake.
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.
Demystifies the concept of Data Lakes for a business audience and technology decision-makers. It provides a straightforward introduction to what Data Lakes are, their potential benefits, and how to approach building one. It's a good starting point for those who need a high-level understanding without getting into deep technical details.
Python widely used language in data engineering and for interacting with Data Lakes. provides a practical guide to building data pipelines using Python, covering essential concepts and best practices. It's valuable for those who need to implement data ingestion and processing tasks for a Data Lake using Python.
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.
Apache Airflow popular tool for orchestrating data pipelines, which are essential for managing data flow into and out of Data Lakes. provides an introduction and guide to using Airflow, offering practical examples for building and maintaining data workflows. It's a useful resource for implementing the operational aspects of a Data Lake.
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.
Practical guide to data connectivity. It covers a wide range of topics, from the basics of data connectivity to advanced techniques for handling complex data types. This book valuable resource for anyone working with data, regardless of their level of expertise.
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.
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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.
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.
Practical guide to the Linux command line. It covers everything from basic commands to advanced topics like file management and networking.
Managing data at scale core challenge that Data Lakes address. provides best practices for designing enterprise data architectures, offering valuable insights into how Data Lakes fit into a larger data management strategy. It's relevant for understanding the organizational and architectural considerations for Data Lakes.
Offers a collection of insights and best practices from experienced data engineers on a wide range of topics, many of which are relevant to Data Lakes. It provides practical advice and different perspectives on common challenges in data engineering, including aspects of building and managing data platforms like Data Lakes.
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.
Focused on the ETL (Extract, Transform, Load) process, this book is highly relevant for understanding how data is moved and prepared for analysis, including data that might reside in a Data Lake. While a classic in data warehousing, the principles of ETL are fundamental to Data Lake operations and data pipelines. is valuable as a reference for data integration techniques.
Understanding the internals of database and distributed data systems is beneficial for comprehending how Data Lakes and the technologies built around them function. provides a deep dive into these concepts, offering valuable technical background for those looking to optimize and troubleshoot Data Lake infrastructure.
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.
Classic guide to the sed and awk command-line tools. It covers everything from basic text processing to advanced topics like regular expressions and scripting.
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.
Provides a practical guide to building a data warehouse using SQL Server. While focused on data warehousing, the principles of data modeling, ETL, and data quality discussed are relevant to managing structured data within a Data Lake or a Data Lakehouse. It can serve as background reading for understanding traditional data integration concepts.
Gentle introduction to the Bash command-line shell. It covers everything from basic commands to advanced topics like scripting and job control.

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