Data Quality 101: Data Quality Overview

Length of Workshop:
Half-day

General Overview:
This introductory class on data quality is designed to give attendees a general overview on the importance of data quality, why it's difficult to achieve and why it's worth the collective effort for your organization to insist on clean, high-quality data.

Leader: Tom Redman

Workshop Goals:
To provide background and direction needed to start a successful data quality program. Specifically, to:
  • Discuss why high-quality matters
  • Define "data quality" and other important terms
  • Discuss the competing approaches to data quality management
  • Review "social issues" that prevent organizations from having excellent data
  • Learn how those with the best quality data do it.


Intended Audience:
This workshop is valuable for everyone in an organization who "touches" its data, from data entry people to marketers, business managers, and IT professionals.

Outline/At a Glance:
The Pain Caused by Poor Data
  • Group Exercise: Personal Examples
  • Poor Quality Data are Insidious
  • Exercise: The Pain in Your Organization


What are Quality Data?
  • Data Quality Defined
  • Most Common "Dimensions of Data Quality"
  • Data Defined
  • The Organic Nature of Data In Organizations


Approaches to Data Quality
  • Lessons from the Lake and Stream
  • Predictable Outcomes
  • Exercise: Characterize Your Organization's Approach


"So, Why Doesn't Everyone Have Perfect Data?" or Social Barriers to Improvement
  • Everything about Data is Political
  • Examples of Social Issues
  • Exercise: Social Issues in Your Organization


Second-Generation Data Quality Systems
  • Best Practice
  • Management of Data Quality
  • Technical Elements
  • A Note on the Organizational Chart
  • Exercise: Customers and Quality


"What Did He Say?" Wrap-Up
  • Most Important Points


For more information on bringing this workshop to your organization, contact Dennis Crowley by phone at +1 781 641 5125, by fax at +1 781 648 1950, or by e-mail at sales@cutter.com.
Data Quality 101: Data Quality Overview

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