Detailed Course Outline
Module 00 - Introduction
(in English)
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
- Critical Data Integration Capabilities
- Cloud Data Fusion user interface components
Module 02 - Building Pipelines
- Cloud Data Fusion architecture
- Basic concepts
- Data pipelines and directed acyclic graphs (DAG)
- Pipeline Life Cycle
- Designing pipelines in Pipeline Studio
Module 03 - Designing Complex Pipelines
- Branches, merges and joins
- Actions and Notifications
- Error handling and macros Pipeline configurations, scheduling, import and export
Module 04 - Pipeline Execution Environment
- Scheduling and triggers
- Runtime environment: Compute profile and provisioners
- Pipeline Monitoring
Module 05 - Building transformations and preparing data with Wrangler
- Wrangler
- Guidelines
- User-defined directives
Module 06 - Stream Connectors and Pipelines
- Understand the data integration architecture.
- List the different connectors.
- Use the Cloud Data Loss Prevention (DLP) API.
- Understand the streaming pipeline reference architecture.
- Build and run a streaming pipeline
.
Module 07 - Metadata and Data Lineage
- Metadata
- Data lineage
Module 08 - Summary
- Course summary