Oracle Enterprise Data Quality 12c: Match and Parse training 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.And Profile, Audit and Operate topics cover on how to profile the quality of a set of data. Expert Oracle University instructors will explore Oracle Enterprise Data Quality's user interface and how to use its profiling tools to delve into data and quickly identify inconsistencies, missing data and other problems.
Preview
By the end of this training you will 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.
Identify data problems and check data validity.
Import and export data.
Check data quality using audit processors.
Create data quality processes and jobs to run in batch and real-time.
Reuse configuration in different processes.
Transform data for auditing.
Set up audit checks on the data and export the data.
Deploy strategies to re-use your work by publishing processors, creating and importing packages and making use of data interfaces and run profiles.
Understand Oracle Enterprise Data Quality's Server Console user interface and its Customer Data Extension Pack.
Course Contents
Day 1
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 Lists and Fuzzy (inexact) Matching
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
Day 2
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
Introduction to Case Management
Overview of Case Management
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
Introduction to the Customer Data Servcies Pack
Customer Data Services Pack Overview
Parse Overview
About Business Uses of Parsing
Parsing in Oracle Enterprise Data Quality
Day 3
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
Optional- Case Studies
Discussing Parse Case Study
Discussing Overall Enterprise Data Quality Case Study
Enterprise Data Quality Overview
Overview of Enterprise Data Quality and its Features
Overview of High-level architecture
Day 4
Director User Interface and its Key Objects
About Process Canvas, Tool Palette, Results Browser and Project Browser
Saving Results to a Results Book
Setting up Projects, Data Stores, Snapshots and Processes
Profile
Using the Quickstats Profiler for a Fast Overview of Data
Identifying Trends with the Frequency Profiler
Examining Outliers with the Max / Min Profiler
Profiling Patterns
Assessing Record Completeness
Audit
Using Audit Processors to Check Your Data
Understanding Flags
Using Audit Processors to Branch Processes
Transform
Using Lookup and Return to Enrich Your Data
Using the Group and Merge Processor
Transforming Data to enable better auditing
Writing and Exporting Data
Using the Writer
Setting up an Export
Automated Processing: Jobs
Configuring and scheduling jobs
Day 5
Re-using Your Work: Publishing, Packaging and Copying
Publishing processors
Creating and importing packages
Introduction to the Customer Data Extension Pack
Understanding the use of Customer Data Extension Pack
Installing the Customer Data Extension Pack
Examining a Customer Data Extension Pack Processor
Real-Time Processing Via Web Services
Configuring a web service within Enterprise Data Quality
Creating and testing a real-time process
Data Interfaces
Introducing Data Interfaces
Creating a data interface
Using a data interface in a process
The Server Console
Overview of the Server Console user interface
Running, Scheduling and Monitoring jobs from the Server Console user interface
Run Profiles
Overview of Run Profiles
Creating a Run Profile
Running a job with a Run Profile
Sampling
Sampling options
Introduction to Case Management
Overview of Case Management Functionality
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