Data Integration with Google Cloud Data Fusion Training
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Data Integration with Cloud Data Fusion

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Learn to streamline and automate data integration with Google Cloud Data Fusion. Build scalable, code-free data pipelines for analytics and machine learning with ease.

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Overview

The Data Integration with Google Cloud Data Fusion training provides a comprehensive understanding of how to integrate, transform, and manage data using Cloud Data Fusion. This course explores its visual interface for building ETL pipelines, integrating data from diverse sources, and preparing datasets for analytics or machine learning. With hands-on labs and real-world scenarios, you’ll gain the skills to create scalable, code-free data integration workflows. Perfect for data engineers and professionals seeking to simplify data management on Google Cloud.

Key Features

  • Comprehensive Curriculum
  • Diverse Source Integration
  • No-Code Workflows
  • Real-Time Data Processing

Curriculum

Study Plan

1Module 1: Introduction to data integration and Cloud Data Fusion
  • Data integration: what, why, challenges
  • Data integration tools used in industry 
  • User personas 
  • Introduction to Cloud Data Fusion
  • Data integration critical capabilities 
  • Cloud Data Fusion UI components 
2Module 2: Building Pipelines
  • Cloud Data Fusion architecture 
  • Core concepts 
  • Data pipelines and directed acyclic graphs (DAG) 
  • Pipeline Lifecycle
  • Designing pipelines in Pipeline Studio  
3Module 3: Designing complex pipelines
  • Branching, Merging and Joining
  • Actions and Notifications 
  • Error handling and Macros
  • Pipeline Configurations, Scheduling, Import and Export  
4Module 4: Pipeline execution environment
  • Schedules and triggers 
  • Execution environment: Compute profile and provisioners 
  • Monitoring pipelines
5Module 5: Building Transformations and Preparing Data with Wrangler
  • Wrangler 
  • Directives
  • User-defined directives
6Module 6: Connectors and streaming pipelines
  • Understand the data integration architecture. 
  • List various connectors
  • Use the Cloud Data Loss Prevention (DLP) API
  • Understand the reference architecture of streaming pipelines
  • Build and execute a streaming pipeline                         
7Module 7: Metadata and data lineage
  • Metadata 
  • Data lineage

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