phone IND : +91 8725090910 USA : +1 845 622 2228

email learnosign2020@gmail.com

IICS: Cloud Data Integration Services

What Will I Learn?

This course is applicable to version R33. Learn the fundamentals of Informatica Intelligent Cloud Services (IICS), including the architecture and data integration features, synchronization tasks, cloud mapping designer, masking tasks and replication tasks. This course enables you to operate and manage user security, secure agents, and monitor tasks and resources in IICS.

Learning Objectives

  • After successfully completing this course, students should be able to:
  • Describe Informatica Cloud Architecture
  • Install the secure agent and create connections
  • Create Synchronization task
  • Use Cloud Mapping Designer to create Mappings and Mapping Tasks
  • Create a Replication task
  • Create a Masking task
  • Create a Mass Ingestion task
  • Create Taskflows
  • Use IICS REST web services for data integration
  • Use Intelligent Structure Model to parse data
  • Handle exceptions
  • Use advanced data integration features to optimize performance of jobs
  • Automate and monitor tasks
  • Configure advanced administration settings in IICS
  • Distinguish users and groups
  • Configure custom roles in IICS
  • Manage Assets
  • Configure SAML setup
  • Use Discovery IQ features to manage, monitor, and troubleshoot integration processes

Prior Knowledge

Need to process large volumes of data, but want to avoid managing servers or acquiring additional big data skills? Informatica’s Cloud Data Integration Elastic service combines a serverless Spark engine with dynamic scaling and automation for streamlined cloud-based processing.

The Cloud Data Integration Elastic secure agent starts the cluster and automatically pushes the jobs to the cluster for processing.

The Cloud Data Integration Elastic secure agent dynamically scales the cluster up or down based on demand and consumption.

The advanced Spark serverless compute engine enables processing of large volumes of data with high concurrency.

Monitor the cluster and the jobs through the administrative dashboard, including activity logs and lifecycle graphs.

Module1 - Informatica Cloud Overview

  • 1.1 Informatica Intelligent Cloud Services (IICS) as an iPaaS solution
  • 1.2 Informatica Cloud Terminologies
  • 1.3 Informatica Cloud Architecture
  • 1.4 CDI Assets
  • 1.5 CDI Components
  • 1.6 Lab: Navigating the IICS interface

Module2 - Runtime Environments and Connections

  • 2.1 Runtime Environments
  • 2.2 Secure Agent Architecture
  • 2.3 IICS Log Files
  • 2.4 Connections
  • 2.5 Connection Types
  • 2.6 Creating Connections
  • 2.7 Lab: Creating a Salesforce connection
  • 2.8 Lab: Creating a Flat File connection
  • 2.9 Lab: Creating an Oracle connection

Module3 - Synchronization Task

  • 3.1 Synchronization Task – Target Step
  • 3.2 Synchronization Task – Data Filters Step
  • 3.3 Synchronization Task – Field Mapping Step
  • 3.4 Synchronization Task – Schedule Step
  • 3.5 Activity Monitor
  • 3.6 Lab: Creating a Synchronization Task
  • 3.7 Lab: Using Filter, Expression, and Lookup in a Synchronization Task
  • 3.8 Lab: Creating a Synchronization Task with Multiple Object Source Type
  • 3.9 Lab: Using Pre and Post SQL commands in a Synchronization Task
  • 3.10 Synchronization Task Overview
  • 3.11 Synchronization Task – Definition Step
  • 3.12 Synchronization Task – Source Step

Module4 - Cloud Mapping Designer – Basic Transformations

  • 4.1 Cloud Mapping Designer Overview
  • 4.2 CLAIRE Transformation Recommendations
  • 4.3 Mapping Designer Terminologies
  • 4.4 Source Transformation
  • 4.5 Target Transformation
  • 4.6 Filter Transformation
  • 4.7 Joiner Transformation
  • 4.8 Expression Transformation
  • 4.9 Lookup Transformation
  • 4.10 Field Rules
  • 4.11 Best Practices for Creating Mappings
  • 4.12 Lab: Creating a mapping using basic transformations

Module5 - Advanced Transformations and Mapping Tasks

  • 5.1 Aggregator Transformation
  • 5.2 Normalizer Transformation
  • 5.3 Java Transformation
  • 5.4 SQL Transformation
  • 5.5 Union Transformation
  • 5.6 Lookup Transformation
  • 5.7 Rank Transformation
  • 5.8 Sequence Generator Transformation
  • 5.9 Data Masking Transformation
  • 5.10 Cleanse Transformation
  • 5.11 Rule Specification Transformation
  • 5.12 Verifier Transformation
  • 5.13 Mapplets
  • 5.14 Mapping Task
  • 5.15 Lab: Using Normalizer, Aggregator, and Rank transformations in a mapping
  • 5.16 Lab: Creating a mapping using Unconnected Lookup Transformation
  • 5.17 Lab: Creating a Mapping Task
  • 5.18 Lab: Using Mapplet Transformation

Module6 - Mapping Parameters

  • 6.1 Parameterization use cases
  • 6.2 Adding Parameters to a Mapping
  • 6.3 Creating parameters
  • 6.4 Parameter Types
  • 6.5 Using parameter files
  • 6.6 Parameter Best Practices
  • 6.7 Lab: Performing Complete Parameterization
  • 6.8 Lab: Using Parameter File in a Mapping task
  • 6.9 Lab: Using In-Out parameters for incremental data loading

Module7 - Expression Macro and Dynamic Linking

  • 7.1 Expression Macro
  • 7.2 Dynamic Linking
  • 7.3 Lab: Using Expression Macro in a mapping
  • 7.4 Lab: Using Dynamic Linking in a mapping

Module8 - Replication Task

  • 8.1 Replication Task Overview
  • 8.2 Replication Task Features
  • 8.3 Replication Task: Source and Target Options
  • 8.4 Other Replication Task Options
  • 8.5 Resetting the Target Table
  • 8.6 Generating Non-Unique Index
  • 8.7 Lab: Replicating Data to a Flat File

Module9 - Masking Task

  • 9.1 Masking Task Overview
  • 9.2 Masking Task: Source and Target Options
  • 9.3 Data Subset: Row Limits and Data Filters
  • 9.4 Field Masking Rules
  • 9.5 Masking Rule Types
  • 9.6 Refresh Masking Task metadata
  • 9.7 Reset a Masking Task
  • 9.8 Masking Best Practices
  • 9.9 Lab: Creating a Masking Task

Module10 - Mass Ingestion Task

  • 10.1 Mass Ingestion Task overview
  • 10.2 Mass Ingestion task sources and targets
  • 10.3 File processing actions
  • 10.4 Configuring a Mass Ingestion Task
  • 10.5 Lab: Creating a Mass Ingestion Task

Module11 - Taskflows

  • 11.1 Taskflow overview
  • 11.2 Linear Taskflows
  • 11.3 Taskflow Steps
  • 11.4 Taskflow Templates
  • 11.5 Using REST APIs
  • 11.6 Invoke a Taskflow through a File Listener
  • 11.7 Lab: Creating a Parallel Taskflow
  • 11.8 Lab: Passing in-out parameters in a Taskflow
  • 11.9 Lab: Invoking a Taskflow through a File Listener

Module12 - Advanced Options

  • 12.1 Primary Key Chunking
  • 12.2 Lookup SQL Override

Module13 - Hierarchical Connectivity

  • 13.1 Web Service transformation
  • 13.2 REST V2 Connector
  • 13.3 Hierarchical Schemas
  • 13.4 Hierarchy Parser Transformation
  • 13.5 Hierarchy Builder Transformation
  • 13.6 Lab: Creating a mapping using a REST V2 connector
  • 13.7 Lab: Using Web Services transformation in a mapping
  • 13.8 Lab: Creating a mapping using Hierarchy Parser Transformation
  • 13.9 Lab: Creating a mapping using Hierarchy Builder Transformation

Module14 - Intelligent Structure Model

  • 14.1 Intelligent Structure Model
  • 14.2 Intelligent Structure Discovery Process
  • 14.3 Intelligent Structure Example
  • 14.4 Refining a Discovered Structure
  • 14.5 Editing an Intelligent Structure Model
  • 14.6 Using intelligent structure models in Structure Parser transformation
  • 14.7 Lab: Creating an Intelligent Structure Model
  • 14.8 Lab: Using Structure Parser transformation in a mapping

Module15 - IICS APIs

  • 15.1 REST API overview
  • 15.2 Informatica Cloud REST API
  • 15.3 REST API Versions
  • 15.4 Request Header and Request Body configuration
  • 15.5 Return Lists
  • 15.6 RunAJob Utility
  • 15.7 Lab: Running a Mapping task using REST API

Module16 - Exception Handling

  • 16.1 Types of exceptions
  • 16.2 User-defined exceptions
  • 16.3 Non-fatal exceptions
  • 16.4 Default Field Value Setting
  • 16.5 Row Error Logging
  • 16.6 Error handling settings
  • 16.7 Fatal exceptions
  • 16.8 Bad files or Reject files
  • 16.9 Lab: Creating a mapping to handle non-fatal errors

Module17 - Performance Tuning

  • 17.1 Types of Partitions
  • 17.2 Partitioning Rules and Guidelines
  • 17.3 Pushdown optimization overview
  • 17.4 Types of pushdown optimization
  • 17.5 Cross-schema pushdown optimization
  • 17.6 Pushdown optimization user-defined parameters
  • 17.7 Pushdown compatible connections
  • 17.8 Secure agent groups
  • 17.9 Secure agent groups with multiple agents
  • 17.10 Shared secure agent groups
  • 17.11 DTM performance properties

Module18 - Automating and Monitoring Tasks

  • 18.1 Schedules
  • 18.2 Schedule Repeat Frequency
  • 18.3 Schedule Blackout Period
  • 18.4 Monitoring tasks
  • 18.5 Email Notifications
  • 18.6 Event Monitoring
  • 18.7 Lab: Creating a schedule

Module19 - Administration

  • 19.1 Licenses
  • 19.2 Administrator Service
  • 19.3 User Roles (System-defined Roles and Custom Roles)
  • 19.4 Creating a User
  • 19.5 User Groups
  • 19.6 Permissions
  • 19.7 Object-Level Permissions
  • 19.8 Organization Hierarchy
  • 19.9 Sub-Organization
  • 19.10 Importing and Exporting Assets
  • 19.11 Asset Dependency
  • 19.12 Add-on Bundles
  • 19.13 Lab: Configure Administrative settings for your Informatica Cloud org
  • 19.14 Lab: Creating a sub-organization and importing/exporting assets

Module20 - SAML Setup

  • 20.1 Security Assertion Markup Language (SAML) Overview
  • 20.2 SAML requirements
  • 20.3 SAML restrictions
  • 20.4 SAML configuration

Module21 - Discovery IQ

  • 21.1 Discuss Informatica Discovery IQ
  • 21.2 List the features of Discovery IQ