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Discover and Catalog Vertex AI Assets with Dataplex

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn how to catalog and discover Vertex AI assets, such as models and datasets, using Dataplex.

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What's inside

Syllabus

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Focuses on Vertex AI assets, which are essential for managing machine learning workflows and model deployments in a production environment

Uses Dataplex, which helps to centrally manage, monitor, and govern data across data lakes, data warehouses, and data meshes

Presented by Google Cloud, which is recognized for its contributions to cloud computing and its suite of data management tools

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Reviews summary

Practical guide to vertex ai cataloging

According to learners, this lab receives a largely positive score. Students found it to be a great practical exercise offering a hands-on approach to discovering and cataloging Vertex AI assets with Dataplex. The instructions were clear and easy to follow, making it a useful guide for working professionals in MLOps or GCP roles. However, some students noted it assumes prior knowledge of Vertex AI and Dataplex, suggesting it might be challenging for complete beginners. The focus is primarily on demonstrating the step-by-step process rather than in-depth conceptual explanations.

Minimal conceptual explanation

"The explanation of the concepts was minimal, but the focus is clearly on the steps needed to perform the task."

"The core task is demonstrated well, though."

"It focuses more on showing you how to do it rather than explaining the underlying theory."

Highly relevant for professional roles

"Highly relevant for anyone in MLOps."

"Definitely recommend if you need to work with Dataplex and Vertex AI."

"Useful for consolidating understanding relevant to my job."

Steps are easy to follow

"The instructions were clear and easy to follow."

"The steps were logical."

"It walks you through the process step-by-step."

Offers valuable practical experience

"Very practical and hands-on approach to discovering and cataloging Vertex AI assets."

"Fantastic hands-on lab. It walks you through the process step-by-step."

"Good practical exercise. The lab environment was easy to use."

May require familiarity with concepts

"The lab works, but it assumes some prior knowledge of both Vertex AI and Dataplex."

"If you're completely new, some steps might be confusing."

"It might be a bit challenging if you're not already familiar with the services."

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 Discover and Catalog Vertex AI Assets with Dataplex with these activities:

Review Google Cloud Fundamentals

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Reinforce your understanding of core Google Cloud concepts to better grasp how Dataplex integrates with the broader Google Cloud ecosystem.

Browse courses on Google Cloud

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Review the core services offered by Google Cloud.
Familiarize yourself with IAM roles and permissions in Google Cloud.
Understand the basics of networking in Google Cloud.

Cloud Native Data Management

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Understand the principles of cloud native data management and how Dataplex fits into a cloud native data strategy.

View Data Management at Scale on Amazon

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Read the chapters on data lakes, data warehouses, and data pipelines.
Consider how Dataplex can be used to implement the concepts discussed in the book.
Research cloud native data management best practices.

Data Governance: The Definitive Guide

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Understand the broader context of data governance and how Dataplex fits into an organization's overall data strategy.

View Meeting the Challenges of Data Quality... on Amazon

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Read the book's introduction and table of contents to get an overview.
Focus on chapters related to data cataloging, metadata management, and data quality.
Relate the concepts discussed in the book to the features and functionalities of Dataplex.

Three other activities

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Follow Dataplex Quickstart Guides

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Gain hands-on experience with Dataplex by working through official quickstart guides to understand its basic functionalities.

Browse courses on Dataplex

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Complete the Dataplex quickstart guide on the Google Cloud documentation site.
Experiment with different Dataplex features like data discovery and data quality.
Document your findings and any challenges encountered.

Document Your Dataplex Learning Journey

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Solidify your understanding of Dataplex by creating a blog post or documentation that explains how to use it with Vertex AI.

Browse courses on Dataplex

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Choose a specific aspect of Dataplex and Vertex AI integration to focus on.
Write a clear and concise explanation of the chosen topic.
Include code snippets and screenshots to illustrate your points.
Publish your documentation on a blog or share it with the community.

Build a Data Cataloging Pipeline with Dataplex

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Apply your knowledge by building a data cataloging pipeline that automatically discovers and catalogs Vertex AI assets using Dataplex.

Browse courses on Dataplex

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Design a data pipeline that extracts metadata from Vertex AI assets.
Configure Dataplex to automatically discover and catalog the extracted metadata.
Implement data quality checks to ensure the accuracy and completeness of the cataloged data.
Create a dashboard to visualize the cataloged assets and their metadata.

Career center

Learners who complete Discover and Catalog Vertex AI Assets with Dataplex will develop knowledge and skills that may be useful to these careers:

Machine Learning Operations Engineer

Machine Learning Operations Engineers are responsible for deploying and maintaining machine learning models. Learning how to catalog and discover Vertex AI assets using Dataplex is extremely relevant to the work a Machine Learning Operations Engineer does, particularly when it comes to managing model versions and associated datasets. This work involves ensuring that models are properly tracked and accessible for development, deployment, and monitoring which this course helps with. Taking this course helps learn how to manage assets, which is a task vital to this role.

See salaries and explore the career path for Machine Learning Operations Engineer

AI Platform Specialist

An AI Platform Specialist focuses on the management and maintenance of AI platforms. This course teaches how to catalog and discover Vertex AI assets, a key skill for those working with AI platforms, using the tool Dataplex. This role requires a deep understanding of how AI models and datasets are organized and managed within a platform, which this course helps with. This course provides an introduction to specific tools and their usage, which is advantageous in this role.

See salaries and explore the career path for AI Platform Specialist

Machine Learning Engineer

A Machine Learning Engineer develops and implements machine learning models. This course helps a Machine Learning Engineer by teaching how to catalog and discover Vertex AI assets, which is beneficial for tracking and managing the model lifecycle. This role benefits from practical knowledge of data management tools. Taking this course builds up skills that are very pertinent to the machine learning development process.

See salaries and explore the career path for Machine Learning Engineer

Data Governance Analyst

A Data Governance Analyst works to establish and enforce policies for data management. This role requires an understanding of data cataloging and discovery, which this course provides by teaching how to catalog Vertex AI assets using Dataplex. This course offers insight into the tools used to maintain data quality and availability. This course is useful for those looking to enter the field of data governance.

See salaries and explore the career path for Data Governance Analyst

Analytics Engineer

An Analytics Engineer focuses on building and maintaining data pipelines and infrastructure for analytics. This course teaches how to catalog and discover Vertex AI assets, which can help an Analytics Engineer in making sure that data is organized for use in analytics projects. This role needs to access and understand metadata about datasets and models. Taking this course provides this practical skill set.

See salaries and explore the career path for Analytics Engineer

Data Steward

Data Stewards oversee the quality and accessibility of data within an organization. This course provides an understanding of how to catalog and discover assets, aiding a Data Steward in their duties. This role requires a strong understanding of metadata management, which this course directly addresses through the specific use of Dataplex with Vertex AI. This course helps build a foundation in the practical aspects of data governance.

See salaries and explore the career path for Data Steward

Data Quality Manager

A Data Quality Manager is responsible for ensuring accuracy and reliability of data. Learning to catalog and discover assets using Dataplex, as this course describes, can help in understanding how data is managed. This role needs to maintain consistency and quality, which is aided by being able to easily find and understand the data assets. The practical skills from this course helps a Data Quality Manager.

See salaries and explore the career path for Data Quality Manager

Data Catalog Specialist

A Data Catalog Specialist focuses on organizing and maintaining metadata for various data assets. The process of cataloging and discovering Vertex AI assets, such as models and datasets, using Dataplex, as taught in this course, directly applies to the core responsibilities of a Data Catalog Specialist. This role involves making data easily discoverable and understandable for other team members. This course provides hands-on experience in using a specific tool for cataloging, which is an advantage for those seeking this role. This course may be useful to anyone looking to enter this role.

See salaries and explore the career path for Data Catalog Specialist

Cloud Solutions Engineer

A Cloud Solutions Engineer is involved in implementing and supporting cloud-based solutions. This course provides a hands-on experience with cataloging and discovering Vertex AI assets using Dataplex, a task which one might be responsible for in this role. This role requires experience with cloud-based data infrastructure, and this course provides a hands-on introduction.

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Cloud Data Engineer

A Cloud Data Engineer designs, builds, and maintains data infrastructure in the cloud. The skills obtained from this course, such as cataloging and discovering Vertex AI assets with Dataplex, directly apply to the tasks of a Cloud Data Engineer who is expected to manage cloud based machine learning resources. This role requires knowledge of various cloud services, which this specific course gives hands-on experience with. This course may be useful to those taking on this role.

See salaries and explore the career path for Cloud Data Engineer

Solutions Architect

A Solutions Architect designs and plans technology solutions for various business problems. The ability to catalog and discover Vertex AI assets, as covered in this course, is very relevant when designing AI-driven solutions. This role needs a comprehensive understanding of how different pieces of technology fit together, and understanding data management is crucial to this. This course provides practical skills with a specific tool.

See salaries and explore the career path for Solutions Architect

Artificial Intelligence Consultant

An Artificial Intelligence Consultant advises clients on the implementation of AI solutions. Understanding how to catalog and discover Vertex AI assets using Dataplex, as taught in this course, provides a practical perspective on managing and organizing AI resources. This knowledge helps an Artificial Intelligence Consultant recommend optimal data management practices. This course may be useful to those consulting on such technologies and implementations.

See salaries and explore the career path for Artificial Intelligence Consultant

Data Analyst

A Data Analyst analyzes data to extract meaningful insights. Although this course does not directly teach data analysis, the skills in cataloging and discovering data assets using Dataplex can help a Data Analyst find the right data needed for such analysis. This course teaches how to organize and identify assets, which is useful for any professional working with data. This course may be useful to those beginning a career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Research Scientist

A Research Scientist may use machine learning models as part of their research. Knowing how to catalog and discover Vertex AI assets, as taught in this course, is helpful for managing data and models used in research projects. This role may require an advanced degree such as a master's degree or PhD. This course may help researchers who use machine learning.

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Database Administrator

A Database Administrator manages and maintains databases. Although this course is not directly about database maintenance, the skills in cataloging and discovering assets using Dataplex, as taught in this course, are helpful in understanding how data is organized. This role deals with a company's data assets and this course can help them understand how to maintain organization. This course may be useful to those in this role.

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Reading list

We've selected two 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 Discover and Catalog Vertex AI Assets with Dataplex.

Meeting the Challenges of Data Quality Management

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Provides a comprehensive overview of data governance principles and practices. It is useful for understanding the broader context of Dataplex and how it fits into an organization's overall data strategy. While not directly focused on Dataplex, it provides valuable background knowledge for understanding the importance of data cataloging and discovery.

Meeting the Challenges of Data Quality Management

Paperback

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Meeting the Challenges of Data Quality Management

Kindle Edition

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Data Management at Scale

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Provides a good overview of cloud native data management principles. It is helpful for understanding the architectural patterns and best practices for building data-intensive applications in the cloud. While it does not focus specifically on Dataplex, it provides a valuable context for understanding how Dataplex fits into a cloud native data strategy. This book is more valuable as additional reading than as a current reference.

Data Management at Scale

Kindle Edition

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