logo


your one source for IT & AV

Training Presentation Systems Services & Consulting Cloud Services Purchase Client Center Computer Museum
Arrow Course Schedule | Classroom Rentals | Student Information | Free Seminars | Client Feedback | Partners | Survey | Standby Discounts

IBM InfoSphere QualityStage Essentials v11.5

SS Course: 44953

Course Overview

TOP

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.

                                                                  

Scheduled Classes

TOP

What You'll Learn

TOP

- 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

    Outline

    TOP
    Viewing outline for:

    Prerequisites

    TOP

    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.

        Who Should Attend

        TOP

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

          Next Step Courses

          TOP