trainocate-ibm-training-b
Home > Vendors > IBM > 2m213g

2M213G - IBM InfoSphere QualityStage Essentials v11.5

Overview

Duration: 4 days

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.

Objectives

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

Audience

  • Data Analysts responsible for data quality using QualityStage

  • Data Quality Architects

  • Data Cleansing Developers

Content

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

 

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.

Certification

Schedule

Show Schedule for:




Enquire Now
 
 
 
 
By clicking "Submit", I agree to the Terms Of Use and Privacy Policy