Issue list best practices
Hi,
I am starting a data migration/cleansing project and as each entity is analyzed and validated with data quality rules, any failing rows are sent to an issue list. That issue list is then shared with business leads to determine best approaches to fixing the data. There will be approx. 70 entities that we will working with - so that's a possible 70 issue lists.
I wanted to create 1 single dataset that captures metrics after each time the issue list is updated (e.g. 3 new, 12 resolved, 10 ignore for the issue list ENTITY1 etc) that we can share with PowerBI and present in a dashboard (new issues over time or listing entities with new issues). I wanted to do this metrics collection in a reusable workflow but issue lists are not selectable on runtime like other datasets are.
Any tips on issue list management and set-up would be much appreciated.
Comments
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Thanks for providing the detail. Does each issue relate to one 'entity' or multiple? Rather than 70 separate issue lists (which adds to the administration) can you instead add a lookup column tagging the row/issue with the entity/entities impacted. Filtering on this column, using a Workflow parameter, will allow you to generate results per entity.
A schedule running the Workflow 70 times! with each of the 70 parameters to filter the data sounds possible, but at these volumes you might be better using the API to call the Workflow programmatically.
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My initial thought was to use one issue list and put the entity name into the 'origin' field, but I backed off that as I wasn't sure what performance would be like. How scalable are issue lists? Thanks
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we've seen it comfortably handle 100k+ issues. Could likely go bigger depending on the resources your machine has and what else is being processed concurrently.
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Thanks Josh
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