2M413G - IBM InfoSphere Advanced QualityStage v11.5

This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer rule set that you create and use that rule set to standardize the data. You will next build a reference match to relate the cleansed source data to the existing target data.

If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course

Duration: 3.0 days

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Objectives

After completing this course, you should be able to:

  • Modify rule sets
  • Build custom rule sets
  • Standardize data using the custom rule set
  • Perform a reference match using standardized data and a reference data set
  • Use advanced techniques to refine a Two-source match

Content

1. QualityStage Review

  • Course project
  • QualityStage review
  • Data Quality
  • Master Data Management
  • Investigate
  • Standardize
  • Match

2. Structure of a Rule Set

  • Rule Sets and Rule Set files
  • Classes and Classification tables
  • Thresholds
  • Dictionary files
  • Pattern action files
  • Optional tables

3. Creation of a Custom Rule Set

  • Custom Rule Set development cycle
  • Investigate data file
  • Parsing
  • SEPLIST/STRIPLIST updates

4. Initial Investigation of Data to Be Standardized

  • Word Investigation
  • Pattern report
  • Token report

5. Classification Table

  • Create the Classification Table
  • Classification schema
  • What to classify
  • Process
  • Resulting Classification File with Legend
  • Pattern review: refining the Classification Table

6. Pattern Action File

  • Pattern Action Language
  • Development of Pattern Action Sets
  • Refining Pattern Action Sets
  • Investigation of Standardized Results

7. Standardization Rules Designer

  • What is Standardization Rules Designer or SRD?
  • Using the SRD
  • SRD work areas
  • Rule Set revision and selection
  • Embedded assistance

8. Match Frequency

  • Match frequency job
  • Column mapping
  • Match frequency data set
  • Using match frequencies in a match job

9. Two-Source (Reference Match) Advanced Implementation

  • Create a reference match between standardized product data and warehouse data
  • Refine the match results using the description fields of the standardized product data and the warehouse data.

Audience

The intended audience for this course are:

  • QualityStage programmers
  • Data Analysts responsible for data quality using QualityStage
  • Data Quality Architects
  • Data Cleansing Developers
  • Data Quality Developers needing to customize QualityStage rule sets

Prerequisites

Participants should have:

  • Compled the QualityStage Essentials course, or have equivalent experience
  • Familiarity with Windows and a text editor
  • Familiarity with elementary statistics and probability concepts (desirable but not essential)

Certification

product-certification

Course Benefits

product-benefits
  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges
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