Improve Data Quality using a simple mechanism which brings everybody involved in the loop

1. Creating A Data Quality
Loop
Using data quality indicators in your (ad-hoc) reports.
Initiate end-user conversations, use IT effectively, to
aim for accurate data

2. Anna - Confronted with
Plummeting sales caused by
incorrect data

3. Data-entry has different priorities
Sysadmin had to
give up on him

4. Insanely Busy .. LTD
Where is Anna? Where is Bert? How can they know of each others existence anyway?
Sales and more

5. Information manager finds a way to bridge
the gap

6. Data quality indicators : indicate suspect
data in reports

7. Indicators placed on top of the report
requested: one or more critical values
indicate the report outcome is suspect
Sales transaction <0 means negative sales
Indicator pointer is relatively related to amount in graph, a %
boundary determines whether it is critical

8. Information consumer can easily drill-
down within the indicator

9. And eventually drillthrough to the
operational system..and start a conversation

10. CONCLUSION
IT is a middleman to realize DQ-indicators instead of middleman of each DQ -incident
Business is watchdog and keeps the conversation and cleansing going

11. HOW TO ESTABLISH?
Functional analysis with business
IT Implements Indicators
When DQ let end-users have the conversation using the drilldown
So they can cleanse and improve at the source instead of within a
black-box like DWH

12. Coming soon on IntelliFlexBI channel : Tech Session - creating versatile DQ-indicators
See my vizify bio!
IntelliFlex
johan@intelliflex.info