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Informatica Data Quality Foundation for Developers 10.x
Duration
4 Days
Course
INPC-185
Available Formats
Classroom Training, Online Training
Course Description
Overview
This Informatica Data Quality Foundation Bootcamp for Developers course provides attendees with an excellent overview of the Informatica Data Quality Developer tool that includes real life exercises to enhance their learning of the tool.Informatica Data Quality Developer is a thick client tool based on Eclipse. It enables developers to profile data, interact and apply all business rules provided by business analysts. Using the Developer, users implement business rules by creating mappings that include in addition to standard ETL transformations, Data Quality specific transformations such as standardization, matching, address validation, parsing and consolidation. Attendees will learn how to apply various strategies to cleanse and improve data quality.
Collaboration with Analysts via the Repository/Metadata will also be discussed and implemented.
Objectives
Audience
- Developers with no Informatica experience
Topics
1. Data Quality Overview
2. Developer Tool: Physical & Logical Data Objects
- Overview
- Create a Physical Data Object
- Relational
- Customized
- Flat File
- Create a Logical Data Object
- Exercise #1 Creating Connections & Import Data source
- Profiling
- Creating Profiling Rules
- Creating and running scorecards
- Exercise #2 Column Profiling in Developer
- Overview
- Objects
- Mappings
- Sources
- Targets
- Linking and Running
- Transformations
- Ports
- Expressions
- Testing
- Expression
- Filter
- Aggregator
- Sorter
- Joiner
- Lookup
- Router
- Union
- Overview
- Creating
- Mapplet Rules
- Overview
- User Reference Table
- Content sets
- Cleanse and standardize the data set using Standardization transformation: Case Converter, Merger, Labeler, Standardizer
- Exercise #3 Data Standardization
- Parser the data set using one of the following methods: Token Parser, tern ParserNER/Probabilistic Model
- Exercise #4 Parsing using Pattern Based Parsing
- Overview
- Reference Data
- Work with Address Validation mappings
- Introducing Matching Concepts
- Data Grouping
- Matching Analysis
- Matching Transformation
- Exercise #5 Apply Matching Techniques - Classic Matching
- IMO vs Classic Matching
- Overview
- IMO configuration
- Exercise #6 Apply Matching Techniques - Identity Matching
- Consolidation transformation
- Automatically consolidate matched records
- Exercise #7 Multi Criteria Matching, Association and Consolidation
- Build a workflow that handle Exception and duplicate records.
- Human Task
- Other Tasks
- Deployment
- Exercise #8 Informatica Data Quality Workflow Using Human Task
- Update and modify the exception/duplicate records through the Analyst tool.
- Comparison
- Weighted Average
- Exporting to PC
- Importing from PC
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Self-Paced Training Info
Learn at your own pace with anytime, anywhere training
- Same in-demand topics as instructor-led public and private classes.
- Standalone learning or supplemental reinforcement.
- e-Learning content varies by course and technology.
- View the Self-Paced version of this outline and what is included in the SPVC course.
- Learn more about e-Learning
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