Oracle Enterprise Data Quality: Match and Parse

Course Fees: $4026.00 excl. GST
Printed Manual: $0.00 excl. GST
Course Duration: 3 days
Course Manual

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This course (based on Oracle Enterprise Data Quality version 9.0) teaches the participants how to configure match processors to find and optionally merge exact and similar (fuzzy) matching records. Participants learn how to create sophisticated match rule hierarchies, configure merge options and review match results. This offering also deals about the different match processors that are available, including those in the Customer Data Extension Pack. Participants also learn to standardize data and see how this can be used to prepare data for matching.
In addition this course introduces the participants to Oracle Enterprise Data Quality's transliteration capabilities and shows how to use and interpret results from the Oracle Enterprise Data Quality Address Verfication server. Participants learn to reach a semantic understanding of free text by using the Phrase Profiler. They also learn techniques to tailor a Customer Data Extension Pack parse processor to extract, standardize and re-structure data from a free text field and also to configure the Parse processor from scratch.

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
Standardise data using a number of Oracle Enterprise Data Quality processors 

This course is based on Oracle Enterprise Data Quality version 9.0.2 .
  • Business Intelligence Developer 
  • Data Warehouse Administrator 
  • End Users Functional Implementer
  • Reports Developer 
  • Sales Consultants 
  • System Analysts 
  • Technical Consultant
Oracle Enterprise Data Quality: Profile, Audit and Operate
  • Use the Address Verification processor and interpret its results 
  • Use transformation processors to standardize data 
  • Configure parse processors. 
  • 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. 
  • Cofigure match processors to identify and if necessary, consolidate matching data records
Match Overview
Discussing Business Examples of Matching
About the Match Processors
What Constitues a Match?

Oracle Enterprise Data Quality Matching Fundamentals
Discussing Inputs to Match
About Mapping Identifiers
Discussing Fundamentals of Clustering
Setting up Simple Match Rules
Browsing Results

Match Rule Hierarchies
Using Multiple Comparisons
Identifying Fuzzy (inexact) Matches
Tuning Match Rules

Clustering
Clustering for Performance
Clustering Strategies
Tuning Clusters

Merge
Discussing Defaults for Merging
Merging Options

Match Review
Discussing Review Groups
About the Match Review Interface

Customer Data Extension Pack Match Processors
About the Match Entities processor
About the Match Individuals processors
About the Match Households processor

Match Case Studies
Enhancing Records
Describing Deduplication

Address Verification
Overview of Address Verification
Using the Address Verification Processor
About Accuracy flags: Interpreting Address Verification Results


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


Parse Overview
About Business Uses of Parsing
Parsing in Oracle Enterprise Data Qualit

The Phrase Profiler
Using the Phrase Profiler
Identifying Common Words and Phrases
Identifying Misplaced Data

Tailoring a Customer Data Extenstion Pack Parse Profiler- Part I
Understanding Tokenization
Using the Classify sub processor

Tailoring a Customer Data Extenstion Pack Parse Profiler- Part II
Using the Reclassify sub processor
Classification vs. Reclassification

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


Parsing from the Ground Up
Profiling and Classification
Reclassification, Selection and Resolutions

Optional- Case Studies
Discussing Parse Case Study
Discussing Overall Enterprise Data Quality Case Study