-ds "dataset_behavioral_dimension" \-rd "2019-07-15" \-d "," \-f "/Users/brian/Documents/synthetic3.csv" \-bd "labcode"
Track the counts for distinct columns or relationships for behavioral analytics on individual column components
-bd "labcode"
Go beyond just tracking distinct values per the entire column.
For example, if you had a column (or multiple columns) that typically contained 5 values and each of those values typically represented 20% of the column.
ColumnA a -> 20 b -> 20 c -> 20 d -> 20 e -> 20
Consider the row count remained 100 and the total distinct values remained 5, but suddenly the proportion of a given value changed drastically.
ColumnA a -> 1 b -> 39 c -> 20 d -> 20 e -> 20
Behavioral dimension would flag that ColumnA value a is represented much less than normal and value b is represented much more than normal.