Cloud Data Integration
for Developers, Advanced

Instructor Led | IDMC Data Integration | 3 days | April 2026 Release

Course Overview

Explore the advanced functionalities of Informatica Intelligent Cloud Services such as using expression macros, dynamic mapping task, file listeners, handling dynamic schema change and errors, performing structure discovery, SQL ELT optimization, partitioning, and using advanced transformation in cloud mapping designers.
This course is applicable to April 2026 Release.

Objectives

After successfully completing this course, students should be able to:

  • Use advanced Transformations in Cloud Mapping Designer
  • Use Macros in a Mapping
  • Create Dynamic Mapping Tasks
  • Handle Dynamic Schema Change
  • Use File Listener for Task Automation
  • Use Hierarchy Builder and Parser Transformations
  • Use Intelligent Structure Discovery
  • Use Unconnected Lookup Transformation in a Mapping
  • Perform SQL ELT Optimization in a Mapping
  • Perform various Types of Partitioning
  • Discuss Performance Tuning in IDMC

Target Audience

  • Developer

Prerequisites

Agenda
Module 1: IDMC Architecture
  • Explain IDMC Architecture
  • New components in IDMC
Module 2: Dynamic Mapping Task
  • Overview of Dynamic Mapping Task
  • Parameters in Dynamic Mapping Task
  • Jobs and Job Groups
  • Configuring a Dynamic Mapping Task
  • Lab: Create a Dynamic Mapping Task
Module 3: Macros
  • Horizontal Macros
  • Expression Macros
  • Vertical Macros
  • Lab: Use a Vertical Macro to Convert the Date Format in a Field
  • Lab: Use a Vertical Macro to Remove Leading and Trailing Spaces
  • Lab: Use a Horizontal Macro to Classify Company Performance
Module 4: User Defined Functions
  • Explain User Defined Functions
  • Create, Edit and Delete UDFs
  • Lab: Creating User Defined Functions
Module 5: Transaction Control Transformation
  • Explain the Transaction Control Transformation
  • Guidelines for using the Transaction Control Transformation
  • Lab: Using a Transaction Control Transformation in a Mapping
  • Lab: Using a Transaction Control Transformation to Output to Multiple Output Files
Module 6: Dynamic Schema Handling
  • Explain Schema Change Handling
  • Dynamic Schema Change Handling
  • Limitations of Dynamic Schema Change Handling
  • Schema Handling Options
  • Lab: Handling Dynamic Schema Change in a Mapping
Module 7: Advanced Taskflow Techniques with File Listener
  • Discuss Advanced Taskflow Techniques
  • Explain File Listeners
  • Configure a File Listener
  • Invoke a Taskflow through a File Listener
  • Lab: Passing Values from Mapping to Mapping
  • Lab: Using a File Listener as a Step
  • Lab: Using a File Listener with a Timer
Module 8: Dynamic Lookup Cache
  • Discuss Dynamic Lookup Cache
  • Field Mapping in Dynamic Lookup Cache
  • Use case of Dynamic Lookup Cache
  • Lab: Static vs. Dynamic Cache: Effects on Data Updates and Inserts

Module 9: Data Ingestion and Replication
  • Data Ingestion and Replication Task Overview
  • Configuring a Data Ingestion and Replication Task
  • Application Ingestion and Replication Task
  • File Ingestion and Replication Task
  • Database Ingestion and Replication Task
  • Streaming Ingestion and Replication Task
  • Demo: Create Database Ingestion and Replication Task
  • Lab: Creating a Streaming Ingestion and Replication Task
  • Lab: Creating a File Ingestion and Replication Task
Module 10: Normalizer Transformation
  • Explain the Normalizer Transformation
  • Describe Normalized Fields
  • Normalizer Filed Mapping
  • Lab: Using a Normalizer Transformation to Convert Repeating Mainframe Data into Relational Format with Aggregation and Ranking
Module 11: Hierarchical Connectivity
  • Hierarchical Schemas
  • Hierarchy Parser Transformation
  • Hierarchy Builder Transformation
  • Velocity Transformation
  • Lab: Using the Hierarchy Parser to Convert Hierarchical Input into Relational Output
  • Lab: Using a Hierarchy Builder in a Mapping to Generate XML Output
  • Lab: Using the Velocity Template
Module 12: Intelligent Structure Model
  • Intelligent Structure Model
  • Intelligent Structure Discovery Process
  • Intelligent Structure Example
  • Refining a Discovered Structure
  • Intelligent structure models based on MS Word file
  • Using intelligent structure models in Structure Parser transformation
  • Demo: Creating an Intelligent Structure Model
  • Lab: Use a Structure Parser Transformation to parse data from a Table in a Document
Module 13: SQL ELT Optimization
  • SQL ELT optimization Overview
  • Types of SQL ELT optimization
  • SQL ELT optimization in Advanced mode
  • Lab: Performing SQL ELT Optimization in IDMC
Module 14: Mapping Partitioning
  • Partitions Overview
  • Types of Partitions
  • Partitioning Rules and Guidelines
  • Lab: Performing Partitioning


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