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• IBM InfoSphere QualityStage Essentials v11.5 KM213G

Overview

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.

Audience

• Data Analysts responsible for data quality using QualityStage

• Data Quality Architects

Data Cleansing Developers

Skills Gained

List the common data quality contaminants

Describe each of the following processes:

§Investigation

§Standardization

§Match

§Survivorship

Describe QualityStage architecture

Describe QualityStage clients and their functions

Import metadata

Build and run DataStage/QualityStage jobs, review results

Build Investigate jobs

Use Character Discrete, Concatenate, and Word Investigations to analyze data fields

Describe the Standardize stage

Identify Rule Sets

Build jobs using the Standardize stage

Interpret standardization results

Investigate unhandled data and patterns

Build a QualityStage job to identify matching records

Apply multiple Match passes to increase efficiency

Interpret and improve match results

Build a QualityStage Survive job that will consolidate matched records into a single master record

Build a single job to match data using a Two-Source match

Prerequisites

Participants should have:

• Familiarity with the Windows operating system

Familiarity with a text editor

Helpful, but not required, would be some understanding of elementary statistics principles such as weighted averages and probability.