C. Lwanga Yonke presented on managing data quality as a process rather than just an end result. He discussed that data quality is best achieved by controlling business processes at the source to ensure data is collected accurately. Yonke proposed several models for managing information quality as a process, including defining accountabilities and assigning information product managers. He emphasized that data quality requires constant vigilance similar to safety and should be viewed as the product of well-defined information production processes.

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, Australia Copyright 2007 C. Lwanga Yonke

6. What is Information Quality Management? It’s MDM! It’s data correction! It’s data profiling! It’s SOA! It’s EIM! It’s data governance!

8. Data Council Set targets for Improvement Quality Planning Defines accountabilities via Deployed to Supports Deployed to Must advance Supports Underlies everything Responsible for meeting Responsible for meeting Monitor conformance using Leads to To better meet Identify “ gaps” using A platform for Data Policy Control Customer Needs Supplier Management Information Chain Management Data Culture Second-Generation Data Quality Systems Tom Redman © 2001 Thomas C. Redman. All rights reserved Quality Planning Improvement Measurement

9. Total Information Quality Management (TIQM) Larry English P6 Establish the Information Quality Environment P5 Correct Data in Source and Control Redundancy P3 Measure Nonquality Information Costs P2 Assess Information Quality P1 Assess Data Definition & Information Architecture Quality Source: English © 2009 INFORMATION IMPACT International, Inc. All rights reserved. P4 Improve Information Process Quality

10. The Ten Steps™ Process Danette McGilvray 8 Correct Current Data Errors 7 Prevent Future Data Errors 1 Define Business Need and Approach 2 Analyze Information Environment 3 Assess Data Quality 4 Assess Business Impact 5 Identify Root Causes 6 Develop Improvement Plans 9 Implement Controls 10 Communicate Actions and Results © 2008 Danette McGilvray, Granite Falls Consulting, Inc. All rights reserved.

15. 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.org References