Data Integration with Cloud Data Fusion (DICDF) – Outline

Detailed Course Outline

Module 00 - Introduction

Module 01 - 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

Module 02 - Building pipelines

• Cloud Data Fusion architecture
• Core concepts
• Data pipelines and directed acyclic graphs (DAG)
• Pipeline Lifecycle
• Designing pipelines in Pipeline Studio

Module 03 - Designing complex pipelines

• Branching, Merging and Joining
• Actions and Notifications
• Error handling and Macros
• Pipeline Configurations, Scheduling, Import and Export

Module 04 - Pipeline execution environment

• Schedules and triggers
• Execution environment: Compute profile and provisioners
• Monitoring pipelines

Module 05 - Building Transformations and Preparing Data with Wrangler

• Wrangler
• Directives
• User-defined directives

Module 06 - 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.

Module 07 - Metadata and data lineage

• Metadata
• Data lineage

Module 08 - Summary

• Course Summary