Build and Govern a Data Mesh with Dataplex on Google Cloud.
- Why get trained: Learn how to use Dataplex, BigQuery, Cloud Storage and data governance tools to build, manage and secure a scalable data mesh architecture.
- Why it matters: Dataplex helps organisations improve data discovery, governance and collaboration across distributed teams while reducing complexity in modern data platforms.
- Who should attend: Data engineers, data architects, data analysts and IT professionals responsible for managing data lakes, analytics platforms and enterprise data governance.
Build practical Google Cloud data governance and data mesh skills with Trainocate Malaysia. HRD Corp Claimable.
Overview
Become data-driven with Google Cloud. Leverage data and gain real-time insights that improve your decision-making and accelerate innovation.
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.
The Google Cloud Professional Data Engineer Certification Program is a comprehensive program that provides the skills you need to advance your career and provides training to help you prepare for the industry-recognized Google Cloud Professional Data Engineer Certification exam administered by Google Cloud.
What’s in the Data Engineer learning path?
- GCPDE: Data Engineering on Google Cloud
- GCP-DWBQ: Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration
- GCP-DICDF: Data Integration with Cloud Data Fusion
- GCP-MTDBQ: Migrating Teradata Users to BigQuery
- GCP-MSFBQ: Migrating Snowflake Users to BigQuery
- GCP-MRSBQ: Migrating Amazon Redshift Users to BigQuery
Advance your career in data engineering and prepare for the Google Cloud Professional Data Engineer Certification exam with this learning path.
Skills Covered
- 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
Prerequisites
- 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.
Target Audience
- Anyone who are interested.
Module 1: Introduction to Dataplex
Topics:
- Modern Data Platforms and Data-Oriented Design
- Pillars of Data Governance
- What is Dataplex?
- Dataplex Capabilities
- Dataplex compared with other products on Google Cloud
Objectives:
- Identify the importance of a modern data platform
- Explain the role of Dataplex on Google Cloud
Module 2: Creating a Data Mesh on Dataplex
Topics:
- What is a data mesh?
- Dataplex concepts
- Creating data lakes and zones
- Assets in Dataplex
Objectives:
- Define key Dataplex concepts
- Configure and set up Dataplex
Module 3: Processing Data on Dataplex
Topics:
- Processing data on Dataplex
- Data preparation tasks
- Ingestion jobs
- Dataflow and Spark tasks
Objectives:
- Understand different data processing options in Dataplex
- Configure and run data preparation tasks on Dataplex
Module 4: Managing Data Security through Dataplex
Topics:
- IAM permissions and roles
- Securing your data lake
- Policy management
- Metadata security
Objectives:
- Secure data lakes, zones, and assets in Dataplex
Module 5: Data Tagging and Data Catalog
Topics:
- Introduction to Data Catalog
- Technical metadata vs. business metadata
- Tags and tag templates
- Entries and entry groups
- Data lineage
Objectives:
- Implement tagging for resources and use tags to search for assets
Module 6: Data Quality and Profiling
Topics:
- Data quality tasks and AutoDQ
- Reporting on data quality
- Data profiling
Objectives:
- Design, execute and report on data quality processes
Module 7: Dataplex Best Practices
Topics:
- Best practices
- End-to-end demo
Objectives:
- Implement best practices for Dataplex
Exam & Certification
Note:Â There is no exam directly associated with this course. However, Google Cloud offers an extensive portfolio of industry-recognized certifications that can help you stand out as a tech professional in 2025 and beyond. Obtaining a Google Cloud certified credential is one of the most effective ways to validate your skills and accelerate your career.
With our expert-led training, you’ll be prepared to:
- Master in-demand capabilities across Cloud, Data & AI, and Cybersecurity, key areas driving global digital transformation.
- Prove your expertise with a globally respected credential recognized by employers worldwide.
- Advance your career by enhancing your credibility, increasing your earning potential, and opening doors to new opportunities.
Explore our full range of Google Cloud certifications and start building the skills that matter today.
Training & Certification Guide
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