Human Error; Human Error Prevention; Human Performance; Human Performance Improvement; Problem Reporting;
Root Cause Analysis; Corrective Action; Process Improvement Tools; Quality and Environmental Management Systems


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Information Quality Improvement

Processes and Best Practices for Business Performance Excellence
James D. Funk

Why this Seminar?

 Poor information quality has become a real impediment to sustained business success and is increasing the resources needed to comply with government regulations and new industry standards. The HIPPA, Sarbannes-Oxley, EU Privacy regulations, and new e-commerce standards have increased the adverse impact of poor information quality. It is important that organizations understand the principles and practices that lead to high quality information. This seminar covers the components of a Total Data Quality Management (TDQM) Program, as developed at MIT, and provides a roadmap for implementing such a program. The seminar also provides examples and a case study that will help you to identify situations in which the various components of the program can be applied to effectively use your organization’s information assets.

Audience

 Business analysts, business intelligence managers, data architects, data warehouse managers, database managers, E-commerce managers and analysts, Information managers, information quality managers, internal auditors, IT managers, quality assurance managers and quality engineers, systems analysts, and technical managers.

Learning Outcomes

 Upon completion of this seminar, one will be able to:

• Define information quality;
• Understand how to determine the dimensions of information quality;
• Understand the three major roles in information quality improvement;
• Understand the conditions and patterns that lead to data defects;
• Understand the Information Production Roadmap;
• Utilize a common framework to define data defect patterns;
• Measure and benchmark the current state of information quality;
• Repair data defects;
• Conduct information quality initiatives;
• Conduct an information quality survey;
• Establish information quality principles and procedures;
• Implement components of a Total Data Quality Management Program.

Outline

 1. The Information Quality Landscape
    o Why information quality is important
    o Typical data quality Issues
    o What has been learned about information quality to date
    o Current information quality research
    o Overview of current information quality techniques

2. Defining Information Quality
    o Intuitive definitions of information quality
    o System definitions of information quality
    o Overview of data deficiencies
    o Dimensions of information quality

3. Information Quality in Context
    o How do organizations define data quality
    o What data quality problems arise in organizations
    o The three data quality patterns
        Intrinsic DQ Pattern
        Accessibility DQ Pattern
        Contextual DQ Pattern
    o The Information Production Roadmap
    o 10 information quality potholes
        Defining the DQ Issue
        Impacts
        Warning signs
        Potential solutions

4. Information Quality Measurement
    o Measurement overview
    o Measurement methodology
    o Measuring subjective perceptions
    o Objective/Quantitative metrics

5. Information Quality Tools
    o Entity-Relationship Diagrams
    o Overview of analysis techniques
    o Data quality surveys
    o Information Production Maps

6. Managing Information as a Product
    o Principles for managing information as a product
    o The information product management life cycle
    o The information product manager
    o Sample exercises

7. Applying Information Quality Fundamentals
    o Information quality principles
        Business not IT owns the data
        Managing data as a product
        Treating data as an asset
        Optimizing the data
    o Information quality best practices
        Keep data structures simple
        Use standard names and definitions
        Develop meaningful definitions
        Treat classification and report structures separately
        Keep labels unique and use them consistently
    o The data-information-knowledge continuum

8. Information Quality Case Study - establishing the appropriate environment

Handouts

 • Copy of Visual Aids
• Copy of exercise materials
• Copy of case study materials
• Certificate of Completion, with Continuing Education Units
Click here to register for the “Information Quality Improvement” Seminar
Click here for James D. Funk's credentials

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