Jul 2nd, 2018. 3 min read
Track data corrections in our data store
When errors are identified in our EDW-like system, they get submitted to this board (grouped by data freezes). One of our team members gets assigned to research the errors and write correction scripts. Once this is completed, the testing process is started, and when that passes, the script is sent to our IT team for implementation in our production system. We also track the script once it is stored in SVN.
We utilize data captures (freeze tables) for much of our 'official' reporting, and these tables get populated with data errors. This template in Monday has allowed us to create a process by which we can upload a set of data errors and assign people to correct them, QA them and finally implement them in our production environment.
Getting started tips
Different data captures (or freeze events) are treated separately. These make up a group of pulses. Each pulse is a separate submission. Generally, these submissions are based on a related group of errors, but this isn't necessary. The person who found the errors creates the pulse, and uploads the file identifying the errors, and what the values should be. They assign the script writer to the pulse, who then will assign the next person as they finish their task, until the file is implemented in production.
The column "SVN Link to Script" tracks the library where the script can be found.
"I don't have to track communication within Outlook. I can look at all of the error submissions in one place."
Why we love this template
The next step is to identify (quantifiably) the errors that occur repeatedly. We can then discuss what we can do to prevent them from happening.
As well, I can check on the progress of error tracking in minutes. And everyone else can as well. I can communicate easily with my team on every correction, and I know that we will be dealing with the same information.
Without this template I would
I would spend far more time tracking all of the information associated with each error submission.
I would also be unsure if my team had the same information. Now, we all see the same thing.
I would have to find a tool as good as Monday to get this job done. We evaluated 15 tools. We didn't find a better one.
Hi I'm Geoff Matthews from Utah Valley University - Institutional Research and this was my story
Hi I'm Geoff Matthews from Utah Valley University - Institutional Research and this is my story, check it out
TW Data Corrections