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IBM InfoSphere QualityStage Essentials v11.5

IBM Course Code: KM213G

This course teaches how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. Students will gain experience by building an application that combines customer data from three source systems into a single master customer record.

GK# 3928 Vendor# KM214G
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Who Should Attend?

  • Data Analysts responsible for data quality using QualityStage
  • Data Quality Architects
  • Data Cleansing Developers

Course Outline

1. Data Quality Issues

  • Listing the common data quality contaminants
  • Describing data quality processes

2. QualityStage Overview

  • Describing QualityStage architecture
  • Describing QualityStage clients and their functions

3. Developing with QualityStage

  • Importing metadata
  • Building DataStage/QualityStage Jobs
  • Running jobs
  • Reviewing results

4. Investigate

  • Building Investigate jobs
  • Using Character Discrete, Concatenate, and Word Investigations to analyze data fields
  • Reviewing results

5. Standardize

  • Describing the Standardize stage
  • Identifying Rule Sets
  • Building jobs using the Standardize stage
  • Interpreting standardize results
  • Investigating unhandled data and patterns

6. Match

  • Building a QualityStage job to identify matching records
  • Applying multiple Match passes to increase efficiency
  • Interpreting and improving Match results

7. Survive

  • Building a QualityStage survive job that will consolidate matched records into a single master record

8. Two-Source Match

  • Building a QualityStage job to match data using a reference match