Data Quality as a Process not Just an End Result                                       C. Lwanga Yonke                    ...
BioC. Lwanga Yonke is a seasoned information quality practitioner and   leader. He has successfully designed and implement...
Session AbstractShort presentation from Lwanga Yonke, followed by  interactive discussion of topics below and more• What i...
Manage Information as a Product                                                • Product, not by-product                  ...
The Information Product        Simplified Example - Maintenance Management Business Processes                             ...
What is Information Quality Management?                                      It’s data                                    ...
What is Information Quality Management?                     My Answer“The total effort to improve the quality of the  info...
Second-Generation Data Quality Systems                            Tom Redman                                              ...
Total Information Quality Management (TIQM)                            Larry English                                      ...
The Ten Steps™ Process                                                    Danette McGilvray                               ...
Total Data Quality Management (TDQM)                             Richard Wang•    Define the information product (IP)•    ...
Managing Information as a Product                             Wang’s Four Principles• Understand information consumers’ ne...
Information Quality Certified Professional (IQCP) Framework                              IAIDQ•    Information Quality Str...
Just Like Safety, Information Quality Requires                         Constant Vigilance        “The journey of a thousan...
References  English, L., (2009). Information Quality Applied: Best Practices for Improving Business Information,          ...
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C. Lwanga Yonke

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C. Lwanga Yonke

  1. 1. Data Quality as a Process not Just an End Result C. Lwanga Yonke Data Quality 2011 Asia Pacific Congress 28 – 30 March 2011 Sydney, AustraliaCopyright 2007 C. Lwanga Yonke
  2. 2. BioC. Lwanga Yonke is a seasoned information quality practitioner and leader. He has successfully designed and implemented projects in multiple areas, including information quality, data governance, business intelligence, data warehousing and data architecture. His initial experience is in petroleum engineering and operations.. An ASQ Certified Quality Engineer, Lwanga earned an MBA from California State University and holds a BS degree in petroleum engineering from the University of California at Berkeley. Lwanga is a founding member of IAIDQ and currently serves as an Advisor to the IAIDQ Board and as a board member for several other non-profit organizations. He is a member of the Society of Petroleum Engineers (SPE), a senior member of the American Society for Quality (ASQ ), and the recipient of the 2008 SPE Western North America Regional Management and Information Award.Copyright © 2011 C. Lwanga Yonke. All rights reserved. 2
  3. 3. Session AbstractShort presentation from Lwanga Yonke, followed by interactive discussion of topics below and more• What it means to manage information quality as a process• Defining information quality management• Various models for information/data quality process management• The case for a process approach• Assigning accountabilities for information quality• Data cleansing: when is a good time?Copyright © 2011 C. Lwanga Yonke. All rights reserved. 3
  4. 4. Manage Information as a Product • Product, not by-product • Traditional product manufacturing is a useful analog to frameBusiness Processes information quality issues• Activities, events• Transactions • The needs of analysis and decision-making must dictate the• Measurements quality of the data we capture • Data quality is best assured at the source, by first controlling the business processes and activities that create data. Transformed/ Transfor- Summarized mation Business Data Information Process Decisions Products Analysis &Raw “Manufacturing”Data Process Decision Implementation $$ -making Information Product Principle Data is an integral product of our business processes. Work is not complete until data resulting from the work is collected and captured, as part of the work process and activities that create or modify it.Copyright © 2011 C. Lwanga Yonke. All rights reserved. 4
  5. 5. The Information Product Simplified Example - Maintenance Management Business Processes Business Data Analysis & • Activities, events Decisions Decision Implementation • Transactions -Making $$ • Measurements •Equipment repair •Equipment histories •Equipment hierarchies •Root cause failure •New equipment installation analysis •Autonomous maintenance •Equipment classes •Reliability reviews •Condition-based •Equipment specifications •Bad actors reviews maintenance •Regulatory and other monitoring data •Mean time •Predictive maintenance between failure •Vibration monitoring •Defects & counter measures analysis •Equipment Improvement •Corrective action plans •Kaizen events •Measurement processes •Vibration data •etc. •etc. •etc.Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  6. 6. What is Information Quality Management? It’s data profiling! It’s data correction! It’s MDM! It’s data governance! It’s EIM! It’s SOA!Copyright © 2011 C. Lwanga Yonke. All rights reserved. 6
  7. 7. What is Information Quality Management? My Answer“The total effort to improve the quality of the information an organization receives, generates, uses and/or provides to others” C. Lwanga YonkeCopyright © 2011 C. Lwanga Yonke. All rights reserved. 7
  8. 8. Second-Generation Data Quality Systems Tom Redman Data Council Defines Must accountabilities advance via Data Policy Data Culture Supports Supports Deployed Deployed to to Underlies Information everything Supplier Management Chain Management Responsible for meeting Responsible for meeting Customer Monitor Needs conformance Identify using To “gaps” better using meet A Leads Quality Measurement Control platform Improvement Improvement Quality Planning to for Planning Set targets for© 2001 Thomas C. Redman. All rights reservedCopyright © 2011 C. Lwanga Yonke. All rights reserved.
  9. 9. Total Information Quality Management (TIQM) Larry English P6 Establish the Information Quality Environment P4 Improve Information P1 P2 P3 Process Assess Data Quality Definition & Assess Measure Information Information Nonquality Architecture Quality Information P5 Quality Costs Correct Data in Source and Control Redundancy Source: English © 2009 INFORMATION IMPACT International, Inc. All rights reserved.Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  10. 10. The Ten Steps™ Process Danette McGilvray 3 7 Assess Prevent Data Future Data 1 Quality Errors 2 6 Define 5 9 Analyze DevelopBusiness Identify Implement Information ImprovementNeed and Root Causes Controls Environment PlansApproach 4 8 Assess Correct Business Current Data Impact Errors 10 Communicate Actions and Results © 2008 Danette McGilvray, Granite Falls Consulting, Inc. All rights reserved. Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  11. 11. Total Data Quality Management (TDQM) Richard Wang• Define the information product (IP)• Measure IP• Analyze IP• Improve IPSource: Fisher et al, 2006. © 2006 MIT Information Quality Program. All rights reserved.Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  12. 12. Managing Information as a Product Wang’s Four Principles• Understand information consumers’ needs• Manage information as the product of a well-defined information production process• Manage the life cycle of information products – Creation, growth, maturity, decline• Appoint an information product manager to manage information processes and productsSource: Fisher et al, 2006. © 2006 MIT Information Quality Program. All rights reserved.Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  13. 13. Information Quality Certified Professional (IQCP) Framework IAIDQ• Information Quality Strategy and Governance• Information Quality Environment and Culture• Information Quality Value and Business Impact• Information Architecture Quality• Information Quality Measurement and Improvement• Sustaining Information QualitySource: Yonke et al, 2011. © 2011 IAIDQ. All rights reserved.Copyright © 2011 C. Lwanga Yonke. All rights reserved.
  14. 14. Just Like Safety, Information Quality Requires Constant Vigilance “The journey of a thousand miles begins with one step” Lao TzuCopyright © 2011 C. Lwanga Yonke. All rights reserved.
  15. 15. References English, L., (2009). Information Quality Applied: Best Practices for Improving Business Information, Processes and Systems, New York: Wiley & Sons. Fisher, C., Lauría, E., Chengalur-Smith, S., Wang, R., (2008). Introduction to Information Quality, MITIQ Press, Boston McGilvray., D., (2008). Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information, Morgan Kaufmann Redman, T. C., (2001). The Field Guide, Digital Press, Inc., New York, NY Redman, T. C. (2008). Data Driven: Profiting from Your Most Important Business Asset, Harvard Business School Press Yonke, C. L., Walenta, C., Talburt, J.R., (2011). The Job of the Information/Data Quality Professional , IAIDQ Web sites International Association for Information and Data Quality (IAIDQ) www.iaidq.org www.iaidq.org/main/fundamentals-process-mgt-imp.shtml LinkedIn www.apac.iaidq.org www.linkedin.iaidq.orgCopyright © 2011 C. Lwanga Yonke. All rights reserved. 15

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