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Oracle Enterprise Data Quality 12c: Match and Parse (D91752)


Duration: 3 days

This Oracle Enterprise Data Quality 12c: Match and Parse training (based on Oracle Enterprise Data Quality version 12.1.3) teaches you how to configure match processors to find and optionally merge exact and similar (fuzzy) matching records. You’ll learn how to create sophisticated match rules, configure merge options and review match results.

Learn To:

  • Configure match processors to identify and optionally merge matching records.
  • Use parse processors to extract key data from free text fields.
  • Use the address verification processor and interpret its results.
  • Standardize data using a number of Oracle Enterprise Data Quality processors.
  • Use and interpret results from the Oracle Enterprise Data Quality Address Verification server.
  • Tailor a customer data extension pack parse processor to extract, standardize and re-structure data from a free text field.
  • Configure the Parse processor from scratch.
  • Reach a semantic understanding of free text by using the Phrase Profiler.
  • Understand EDQ’s Customer Data Services Pack and case management functionality.


Upon completing this course, the learner will be able to meet these overall objectives:
  • Tailor parse and match processors from the Customer Data Extension Pack
  • Explain the need and uses of matching
  • Explain the need and uses of parsing
  • Use the Phrase Profiler
  • Explain the essentials of matching and parsing.
  • Configure match processors to identify and if necessary, consolidate matching data records
  • Use the Address Verification processor and interpret its results
  • Use transformation processors to standardize data
  • Configure parse processors


Module 1: Match Overview
  • Discussing Business Examples of Matching
  • About the Match Processors
  • What Constitues a Match?
Module 2: Oracle Enterprise Data Quality Matching Fundamentals
  • Discussing Inputs to Match
  • About Mapping Identifiers
  • Discussing Fundamentals of Clustering
  • Setting up Simple Match Rules
  • Browsing Results
Module 3: Match Rule Lists and Fuzzy (inexact) Matching
  • Using Multiple Comparisons
  • Identifying Fuzzy (inexact) Matches
  • Tuning Match Rules
Module 4: Clustering
  • Clustering for Performance
  • Clustering Strategies
  • Tuning Clusters
Module 5: Merge
  • Discussing Defaults for Merging
  • Merging Options
Module 6: Match Review
  • Discussing Review Groups
  • About the Match Review Interface
Module 7: Customer Data Extension Pack Match Processors
  • About the Match Entities processor
  • About the Match Individuals processors
  • About the Match Households processor
Module 8: Match Case Studies
  • Enhancing Records
  • Describing Deduplication
Module 9: Introduction to Case Management
  • Overview of Case Management
Module 10: Address Verification
  • Overview of Address Verification
  • Using the Address Verification Processor
  • About Accuracy flags: Interpreting Address Verification Results
Module 11: Standardizing Data
  • Overview of Standarization
  • Overview of Simple Standardization
  • About the Character Replace and Replace Processors
  • About the Pattern Transform and RegEx Replace Processors
  • About the Merge Processor
  • Overview of Transliteration Capabilities
Module 12: Introduction to the Customer Data Servcies Pack
  • Customer Data Services Pack Overview
Module 13: Parse Overview
  • About Business Uses of Parsing
  • Parsing in Oracle Enterprise Data Quality
Module 12: The Phrase Profiler
  • Using the Phrase Profiler
  • Identifying Common Words and Phrases
  • Identifying Misplaced Data
Module 13: Tailoring a Customer Data Extenstion Pack Parse Profiler- Part I
  • Understanding Tokenization
  • Using the Classify sub processor
Module 14: Tailoring a Customer Data Extenstion Pack Parse Profiler- Part II
  • Using the Reclassify sub processor
  • Classification vs. Reclassification
Module 13: Tailoring a Customer Data Extenstion Pack Parse Profiler – Part III
  • Using the Select sub processor
  • Using the Resolve sub processor
  • Creating Exact and Fuzzy Resolution Rules


Who Should Attend
  • Data Warehouse Administrator
  • End Users
  • System Analysts
  • Sales Consultants
  • Technical Consultant
  • Functional Implementer
  • Reports Developer
  • Business Intelligence Developer


  • Familiarity with structured data record
  • Oracle Enterprise Data Quality 12c: Profile, Audit and Operate




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