Business has a fundame ntal problem with data quality. In some places it’s merely painful; i n others, it’s nearly catastrophic. Why is the problem so pervasive? Why does it never seem to get fixed? Perhaps we’ve been thinking abou t the problem wrong. It's time for a fresh look.
\nThe central fl aw in the long-running discussion over data quality is literally its focus on ‘data.' Stored data is merely the system or database residue o f things that have already happened in the business, a memory of past event s.
\nTo truly fix ‘data quality’ problems requires a busi ness perspective, a shift in the focus from data design or data cleansing t o what occurs in the business itself. Our sights should be trained squarely on the business activity that results in the data. This discussion introdu ces six dimensions of semantic quality to ensure our aim is true, complemen ted by numerous examples from a large-organization case study.
\nLear ning objectives:
\n\n How semantic quality and data quality differ\n What role concept models need to play\n Where business rules fit in\n How to shape a successful initiative\n How semantic quality relates to business agility\n\n DTSTART:20180424T113000 SUMMARY:The Business View of Data and Data Quality: The Six Dimensions of S emantic Quality DTEND:20180424T122959 LOCATION: See Description END:VEVENT END:VCALENDAR