One of the most rewarding facets of working in both the data quality and business intelligence industry was the look on a manager’s face when they realized that through some basic improvements in their data they were able to open up an entirely new avenue of insight.
In one example, a Telecoms company had historically captured address information for network assets placed in their telecoms exchanges. Because this address data was of minimal use to engineers the quality had deteriorated quite considerably.
I asked the data manager whether we should improve this data and they rejected the idea, “who cares, the engineers know their own patch like the back of their hand”.
As a personal exercise I cleansed the data and added a geocode (a latitude and longitude coordinate) for good measure across several regions.
The following day I loaded up the telecoms engineering data into a data visualization app that allowed me to display the assets on a map and interrogate the data. I then had a brainwave to link in other data that was available such as fault reports and accident reports.
The next step was to show off my new “creation” to the data manager. Simply illustrating their data across another dimension was transformational. They could now get a sense of which areas contained the most valuable equipment, which engineering teams should be sent to a particular fault, which sites created the most accidents – the list went on.
All we had done was add another dimension but by being able to view his data spatially provided instant operational benefits but of course so many more dimensions are available to us through enrichment.
The keys to success were improved data quality, enrichment and obviously the ability to visualize the data. So often we can’t exploit data because the data isn’t timely enough, standardized, formatted or complete. By raising the quality levels we can enrich and create an entirely new perspective that delivers immediate bottom line gains.