In a employee attrition analysis with a table having rowwise data for a (employee like Id, name, Date_Join Date_Relieving Dept Role etc)
eID eName Joining Releiving Dept Married Experience 123 John Doe 10Oct15 12Oct16 HR No 12 234 Jen Doee 01jan16 -NA- HR No 11 (ie she is available)
I can run regression on this data to find the beta coefficients
eID eName Joining Releiving Dept Married Experience 123 John Doe 10Oct15 12Oct16 HR No 12 234 Jen Doee 01jan16 -NA- HR No 11
But I've seen other approach too.. where employee have multiple entries depending on their difference between joining date and current month or relieving month(say Employee A joined in Jan and Left in Dec so he'll have 12 entries updating corresponding columns like experience and marriage etc)
eID eName Dept Married Experience 123 John Doe HR No 0 123 John Doe HR No 1 123 John Doe HR Yes 2 123 John Doe HR Yes 3
can someone tell what differentiate two approaches.. and what are the benefits of this second approach.