Course Outline

Module 1: Course Introduction

  • Course topics
  • Modules and content

Module 2: Data Quality Process Overview

  • Data Quality Management Process Cycle
  • Dimensions of Data Quality 
  • Data Quality Processes 
  • Developer and Analyst Roles and Tools
  • Data Quality Architecture

Module 3: Data Quality Projects and Solutions

  • Customer Data Quality Use Cases
  • Projects that benefit from cleansed and standardized data
  • Data Quality and typical DI/DQ projects
  • Reporting, Gating, and Cleansing projects
  • Solution Architecture for Projects with Data Quality

Module 4: Project Collaboration and Reference Table Management

  • Developer Interface
  • Understanding Analyst projects, Data Objects, Profiles, Rules, Scorecards, Comments and Tags
  • Reference Tables and the Data Quality Process
  • Creating Reference Tables 
  • Lab: Review a project created by an Analyst
  • Lab: Build Reference Tables

Module 5: Working in the Developer Tool

  • Tasks in the Developer Tool
  • Working with Physical and Logical Data Objects
  • Connecting to a table
  • Importing and flat file
  • Creating logical data objects
  • Developer Transformations
  • Mappings and mapplets
  • Content sets and their uses
  • Developer Tips and Tricks
  • Lab: Create a project and assign permissions
  • Lab: Create a connection to an Oracle table and import a flat file
  • Lab: Build a Logical Data Object

Module 6: Profiling, Mapplets and Rules

  • Column Profiling 
  • Mapplets and Scorecards
  • Profiling techniques to debug and improve development 
  • Updating Scorecards with Rules
  • Lab: Create a Rule to measure the Accuracy of data in a field.
  • Lab: Using Informatica Analyst, apply the rule to a Scorecard and review the results.

Module 7: Standardizing, Cleansing and Enhancing Data

  • Standardizing, cleansing, and enhancing data.
  • Mappings that cleanse, standardize, and enhance data
  • Developing standardization mapplets
  • Configuring standardization transformations
  • Lab: Build a Standardization Mapping and Mapplets using Standardization Transformations.

Module 8: Parsing Data

  • The Parsing Process 
  • Parsing techniques 
  • Key parsing transformations
  • Lab: Perform Parsing using a variety of Parsing Transformations
  • Lab: Complete a Standardization Mapping

Module 9: Matching Data

  • Match Data definition
  • The DQ matching process
  • The different stages of Matching 
  • Grouping and its effect on matching
  • Grouping methods
  • Grouping results and refining a grouping strategy 
  • Match algorithms
  • Lab: Build and fine tune a grouping and matching mapping

Module 10: Manual Exception and Consolidation Management

  • Exception and Duplicate record management 
  • Exception Management Process.
  • Populating tables with exception and duplicate record tasks
  • Lab: Build a Mapping that can be used to identify Exception data
  • Lab: Build a Mapping that can be used to identify Duplicate data

Module 11: Building, Managing and Deploying Workflows

  • Workflows and Workflow Tasks
  • Human Tasks and Steps
  • Identifying exception and duplicate records
  • Deploying and executing workflows
  • Verifying Tasks in Informatica Analyst.
  • Lab: Build a Workflow to populate the Analyst Inbox with Exception Tasks
  • Lab: Build a Workflow to populate the Analyst Inbox with Duplicate Record Tasks

Module 12: Deploying: Executing Mappings outside of the Developer tool

  • Deployment options.
  • Mappings as applications
  • Scheduling mappings, profiles, and Scorecards 
  • Lab: Schedule Mappings to run using Informatica Scheduler.

Module 13: Importing and Exporting Project Objects

  • Export/import project use cases
  • Basic and Advanced Import options
  • Exporting a project 
  • Lab: Import a Project using the Basic method.
  • Lab: Import a Project using the Advanced Method.
  • Lab: Export a Project.

Module 14: Troubleshooting

  • Common Developer errors
  • Common Mapping and Transformation configuration issues
  • Common Workflow configuration errors
  • Tips for working with the Developer tool 
  • Lab (Optional): Troubleshoot Mapping configuration issues
 28 Hours

Testimonials (2)