Create a option set for the fields.
Add a list field on the data type, and add the completed fields.
You can then just look for the complete/incomplete fields in the data.
You can also count the number of completed fields in the list, to use as a percentage of data complete.
Like if 6 fileds are added in the list, 60% complete.
Thanks Rishabh, not sure I fully unerstand your solution.
The example is just one entry but in practice each user may have a large variety of data entries so for example 50 Projects or 100 Tasks. The values they can complete are typically unrestricted
(text, date etc.).
A (yes/no)
B (yes/no)
C (yes/no)
D (yes/no)
E (yes/no)
I would like to understand how i can scan all these records in one action, so basically converting a single entry into a list. This would allow me for example to create a .csv with two columns, or identift items where yes is true etc.
Curious to see if anyone has a solution. Seems like something quite trivial.
While the most obvious thing to prevent empty fields is enforcing users to create values on the ‘create’ step. Nevertheless as data in a complex dataset can get changed in various ways there is a tail risk of values getting lost (human error in the design process).
For validation purposes it would be great to have a simple function that could check if a Search for a thing’s list of things contains (a list of) entries that contain empty values
For example my database contains Users.
Users can have:
Name
Email
Photo
Adres
Say i have 20 users and i want to know if any of the 20 users have a missing value.
Setting up this stream once is already cumbersome but doing it across 40 data types with extensive number of data points becomes a significant exercise.