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 the industry
  • User personas
  • Introduction to cloud-based 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
  • Branches, merging and joining
  • Actions and Notifications
  • Error handling and macros
  • Pipeline configurations, scheduling, import and export
Module 04 - Pipeline Execution Environment
  • Scheduling 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

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Module 07 - Metadata and Data Lineage
  • Metadata
  • Data lineage
Module 08 - Summary
  • Course summary