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Course Outline
Module 1: Introduction to the Course
- Course topics
- Modules and content
Module 2: Overview of the Data Quality Process
- 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 benefiting from cleansed and standardized data
- Data Quality in typical DI/DQ projects
- Reporting, Gating, and Cleansing projects
- Solution Architecture for Data Quality projects
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 flat files
- 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
- Definition of Match Data
- 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: Deployment: 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)
The variety of the information shared and the clarity to explain terms in plain English.
Arisbe Mendoza - Fairtrade International
Course - GDPR Workshop
It's a hands-on session.
