Sunday, 14 February 2010

A balanced approach to scoring data quality: Part 6

I wanted to spend a little bit of time concluding this series by discussing how we could visualise the example metrics that were discussed in the past few blog posts.


Wikipedia defines a Dashboard as "an executive information system user interface that (similar to an automobile's dashboard) is designed to be easy to read". This is exactly what we want to achieve when creating a dashboard to present our DQ metrics.

The below diagram shows an example layout for the dashboard:

The 'summary, actions & contact information' section is important, and one which we haven't previously discussed. This section should consist of commentary to allow for further context to be applied to what is contained within the four metric sections of the scorecard. A summary of what has happened in the past month/quarter (since the last scorecard publication), alongside a summary of DQ Management actions to be undertaken in the coming weeks/months. Contact information should always be included to aid ease of further assistance or questions.

Remember the Metrics?

Within the previous posts in the series we looked at a number of example metrics which could be reported upon a DQ scorecard.

Now lets look at an example of how we could bring these metrics together onto our dashboard.

We can even drill down into aspects of the scorecard. For example, each metric within the 'Customer' Section could have an option for the viewer of the dashboard to drill down to gain further insight into that particular metric. The same functionality could exist in the 'Data Dimensions' section. At a high level, we can show a RAG status for each individual business department, or process, and from there we could allow the viewer of the dashboard to drill down in order to ascertain how that RAG status was derived, and which dimensions require particular improvement, or monitoring.

In Conclusion

The balanced approach to scoring data quality that has been discussed within this series can be used as both a vehicle to promote continuous improvement and as an effective performance management tool. I'd be keen to hear your stories of implementing DQ scorecards - successes, failures, lessons learned - so please leave a comment within the series, or contact me directly.

Related Posts

Part 1: Introduction

Part 2: Customer

Part 3: Internal Processes

Part 4: Financial

Part 5: Data Dimensions


Jim Harris said...


Thanks for providing a fantastic series!

All too often, I have seen dashboards deliver:

“All style and no substance.”

In other words, the visualization is well organized and aesthetically pleasing, but the metrics do not measure anything meaningful.

Your series has done an excellent job explaining all of the fundamental aspects required that if more organizations would be willing to follow them, then they might be able to see:

“Data Quality Paradise by the dashboard lights.”



Phil Wright said...

Jim, thanks for the comment - I'm glad you enjoyed the series.

I recently had a conversation with a CFO who wanted me to steer his team away from thinking of dashboards within their BI project due to the very statement you stated above. I think people can often get carried away with 'heat maps', 'dials' and 'flash gadgets' and lose sight of exactly what it is they are trying to measure.

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