Data Quality: Advanced Techniques Training Course

Module 1: Course Introduction

• Course Introduction, Agenda and Overview

Module 2: Developer Review & Join Profiling

• A quick review of Informatica Developer
• Use Enterprise Discovery to create Join Profiles
• Lab: Perform Join Profiling using an Enterprise Discovery Profile

Module 3: Standardizing and Classifying Data

• Review Standardization Techniques
• Build, refine and apply a Classifier Model
• Labs: Create, refine and apply Classifier Model

Module 4: Advanced Parsing Techniques

• What is Probabilistic Labeling and Parsing?
• Build, refine and apply a Probabilistic Model
• Additional Parsing Techniques:
  • Build regular expressions
• Labs: Build, refine and apply a Probabilistic Model
• Lab: Review an example of Advanced Parsing 
• Lab: Generate and test Regular Expressions

Module 5: Grouping & Matching Data

• Additional Grouping Techniques
  • Using Composite keys
• Advanced Matching Techniques
  • Matched pairs outputs
  • Working with Match Mapplets
  • Manipulating the matched data using the Driver ID
  • Perform Dual Matching
• Lab: Create a Match mapping using Matched Pairs 
• Lab: Create and update a Match Mapplet
• Lab: Manipulating Matched Data using the Driver ID
• Lab: Perform Dual Matching using a Master Dataset

Module 6: Automatically Associate and Consolidate Matched Data

• Overview of the Consolidation Process
• Use the Consolidation Transformation to consolidate matched data.
• Use the Association Transformation to link matched data ahead of Consolidation
• Lab: Automatically Consolidate matched data
• Lab: Perform multi-criteria Matching, Association and Consolidation.

Module 7: Task and Workflow Management

• Additional Task and Workflow functionality:
  • Permission settings for data access and editing
  • Notifications including Human Task Notification Variables
  • Setting Timeouts
  • Reviewing Tasks
  • Configuring Workflow Recovery
• Lab: Update the Exception Workflow
• Lab: Review the Consolidation Workflow

Module 8: Processing Updated Exception and Cluster Data

• How to process updated exception records
• How to process consolidated records
• Fields of Interest
• Lab: Create a mapping to process updated exception data
• Lab: Create a mapping to process consolidated data
• Lab: Update and deploy Exception and Cluster Workflows

Module 9: Analyst Tasks

• Update exception and duplicate records in Informatica Analyst
• Lab: Update records and push the Tasks through the Exception Process
• Lab: Update records and push the Tasks through the Consolidation Process

Module 10: Parameterization

• Explain the difference between System and User defined parameters
• Use Parameters in Data Quality mappings.
• Lab: Create a parameterized mapping
• Lab: Build and deploy an Application
• Lab: Create and execute parameter files

Module 11: Performance tips and tricks

• General Installation and Memory Information
• DQ Component Configuration
  • Service Settings
• DQ Transformations
  • Configuration Settings

Module 12: Optional - Data Quality at work

• Learn how Data Quality has been implemented in different projects

Module 13: CRM and Dashboard and Reporting Templates

• Review the CRM and Dashboard and Reporting Templates that are available
• Lab: Review the CRM Template