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info@rislglobal.com - RISLGLOBAL

Informatica Data Quality 9.1 Developer/Analyst
    • Navigate the Developer Tool and collaborate on projects with Analysts using the
       Analyst Tool
    • Perform Column, Rule, Join, Multi object and Mid-Stream Profiling
    • Manage reference tables in the Analyst Tool
    • Design and develop Mapplets
    • Create standardization, cleansing and parsing routines
    • Validate addresses
    • Identify duplicate records
    • Build mappings used to associate and consolidate matched records

 Course Agenda

Introduction to Data Quality Management

Unit 1: Working with Informatica Developer 9

   •   GUI, Mappings, Mapplets, Transformations, Content Sets, Data Objects

Unit 2: Analyst Collaboration

   •   Reviewing information from the Analyst
   •   Comments/Tags
   •   Creating/adding to Reference tables

Unit 3: Developer Profiling

   •   Join Analysis Profiling
   •   Column Profiling
   •   Multi Object Profiling
   •   Mappings and transformations
   •   Mid-stream profiling
   •   Comparative profiling

Unit 4: Data Standardization

   •   Cleanse, transform and parse data
   •   Develop data standardization mapplets and mappings

Unit 5: Address Validation

   •   Reusable AV Transformation
   •   AV Transformation Properties
   •   AV Inputs and Outputs
•   Reusable AV Mapplet

Unit 6: Matching

   •   Grouping data
   •   Analyze Detail Report
   •   DQ Matching
   •   Cluster Analysis Report
   •   Matching Mapplets

Unit 7: Identity Matching

   •   Build Matching mappings using Identity matching
   •   Identity Populations and Strategies

Unit 8: Consolidation

   •   Associate and Consolidate data

Unit 9: Data Quality Assistant

   •   Build Mappings to create and populate the DQA tables
   •   Perform manual Consolidation and Bad Record Management

Unit 10: PowerCenter Integration

   •   Run DQ Mappings in PowerCenter

Unit 11: Object Import/Export

   •   Import Projects using both Basic and Advanced methods
   •   Export Projects

Unit 12: DQ for Excel

   •   Run Data Quality Mappings on Excel Spread sheets

Unit 13: Parameters

   •   How to use Parameters in Data Quality mappings, transformations and reference
       tables

Unit 14: Content

   •   What content is available with IDQ9?
   •   Content Management Service
•      Accelerators
   •      Core Accelerator

Project

   •      Use all that has been covered and apply it to Product Data


Contact info@rislglobal.com for more details

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Informatica data quality 9

  • 1. info@rislglobal.com - RISLGLOBAL Informatica Data Quality 9.1 Developer/Analyst • Navigate the Developer Tool and collaborate on projects with Analysts using the Analyst Tool • Perform Column, Rule, Join, Multi object and Mid-Stream Profiling • Manage reference tables in the Analyst Tool • Design and develop Mapplets • Create standardization, cleansing and parsing routines • Validate addresses • Identify duplicate records • Build mappings used to associate and consolidate matched records Course Agenda Introduction to Data Quality Management Unit 1: Working with Informatica Developer 9 • GUI, Mappings, Mapplets, Transformations, Content Sets, Data Objects Unit 2: Analyst Collaboration • Reviewing information from the Analyst • Comments/Tags • Creating/adding to Reference tables Unit 3: Developer Profiling • Join Analysis Profiling • Column Profiling • Multi Object Profiling • Mappings and transformations • Mid-stream profiling • Comparative profiling Unit 4: Data Standardization • Cleanse, transform and parse data • Develop data standardization mapplets and mappings Unit 5: Address Validation • Reusable AV Transformation • AV Transformation Properties • AV Inputs and Outputs
  • 2. Reusable AV Mapplet Unit 6: Matching • Grouping data • Analyze Detail Report • DQ Matching • Cluster Analysis Report • Matching Mapplets Unit 7: Identity Matching • Build Matching mappings using Identity matching • Identity Populations and Strategies Unit 8: Consolidation • Associate and Consolidate data Unit 9: Data Quality Assistant • Build Mappings to create and populate the DQA tables • Perform manual Consolidation and Bad Record Management Unit 10: PowerCenter Integration • Run DQ Mappings in PowerCenter Unit 11: Object Import/Export • Import Projects using both Basic and Advanced methods • Export Projects Unit 12: DQ for Excel • Run Data Quality Mappings on Excel Spread sheets Unit 13: Parameters • How to use Parameters in Data Quality mappings, transformations and reference tables Unit 14: Content • What content is available with IDQ9? • Content Management Service
  • 3. Accelerators • Core Accelerator Project • Use all that has been covered and apply it to Product Data Contact info@rislglobal.com for more details