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Managing a Data Mesh with Dataplex

SS Course: 70182

Course Overview

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Dataplex is an intelligent data fabric that enables organizations to centrally discover, manage, monitor, and govern their data across data lakes, data warehouses, and data marts. You can use Dataplex to build a data mesh architecture to decentralize data ownership among domain data owners.

In this course, you will learn how to discover, manage, monitor, and govern your data across data lakes, data warehouses, and data marts through guided lectures and independent exercises using sample data.                                                                  

Scheduled Classes

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07/31/25 - TDV - Virtual-Instructor Led - Virtual-Instructor Led (click to enroll)

What You'll Learn

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Identify the importance of a modern data platform
  • Configure and set up Dataplex
  • Secure data lakes, zones, and assets
  • Implement tagging for resources and use tags to search for assets
  • Process data using Dataplex tasks
  • Design, execute and report on data quality processes

Outline

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Viewing outline for:
Modern Data Platforms and Data-Oriented Design
  • Pillars of Data Governance
  • What is Dataplex?
  • Dataplex Capabilities
  • Dataplex compared with other products on Google Cloud
  • Identify the importance of a modern data platform
  • Explain the role of Dataplex on Google Cloud
  • What is a data mesh?
  • Dataplex concepts
  • Creating data lakes and zones
  • Assets in Dataplex
  • Define key Dataplex concepts
  • Configure and set up Dataplex
  • Lab: Provision a Data Mesh using Dataplex
  • Processing data on Dataplex
  • Data preparation tasks
  • Ingestion jobs
  • Dataflow and Spark tasks
  • Understand different data processing options in Dataplex
  • Configure and run data preparation tasks on Dataplex
  • Lab: Standardize Data using Dataplex Tasks
  • IAM permissions and roles
  • Securing your data lake
  • Policy management
  • Metadata security
  • Secure data lakes, zones, and assets in Dataplex
  • Lab: Manage Data Security using Dataplex
  • Introduction to Data Catalog
  • Technical metadata vs. business metadata
  • Tags and tag templates
  • Entries and entry groups
  • Data lineage
  • Implement tagging for resources and use tags to search for assets
  • Lab: Data Catalog and Data Lineage
  • Data quality tasks and AutoDQ
  • Reporting on data quality
  • Data profiling
  • Design, execute and report on data quality processes
  • Lab: Data Quality and Profiling your Data in BigQuery
  • Best practices
  • End-to-end demo
  • Implement best practices for Dataplex
  • Challenge Lab: Managing a Data Mesh with Dataplex

Prerequisites

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Completion of the "Modernizing Data Lakes and Data Warehouses with Google Cloud" and "Building Batch Data Pipelines on Google Cloud" courses in the "Data Engineer" learning path or equivalent experience using Google Cloud.

      Who Should Attend

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      Customers

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