Data Quality: Data Quality Management for the Developer

onDemand | Data Quality | Self-Paced | Version 10.x

Course Overview

Gain the skills and knowledge necessary to implement and automate a data quality assurance process with the Informatica Data Quality platform. In addition, learn how to cleanse, standardize, and enhance data while testing and troubleshooting Data Quality solutions.
This course is applicable for version 10.x

Objectives

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

Describe the Data Quality Management Process
Illustrate the Data Quality Architecture
Differentiate between the Analyst and Developer Roles and Tools.
Navigate the Developer Tool
Collaborate on projects
Perform Column, Rule, Multi-object, Comparative, and Mid-Stream Profiling
Manage Reference Tables
Develop standardization, cleansing, and parsing Mappings and Mapplets
Identify duplicate records using Classic Data Matching
Create and execute Workflows to populate user inboxes with Exception and Duplicate record tasks
Describe the deployment options available when executing Mappings outside of Informatica Developer
Troubleshoot issues that may appear during development

Target Audience

Developer

Prerequisites

None

Agenda

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