Data Warehouse Purge Strategy - HELP

I'm looking at the best way to implement a purge strategy in a dimensional model. The reason to purge is that no personal data can be kept after 4 years, but the users would still want to see counts/facts by no identifying data. For example i couldn't keep a name, but i could keep the gender or employer.

Is it best to do this by depersonalising data e.g. setting certain column to NULL after a number of years, or adopting an aggregate strategy. The data volumes are not huge, but if i go the aggregate route i'm going to be left with quite a lot of duplication, as opposed to just keeping all the detail data and NULL'ing certain columns, after a set time. Doing this aslo avoids any issues with lack of aggregate aware tools.

TIA

Keep it simple, null the columns (or replace with some string, such as 'N/A' or 'Obsolete') you need to drop.

Thanks, it does seem to make a lot of sense to keep it simple, so i will be looking at purging specific data from my selected columns after a certain period of time.

I'll only look at an Aggregate strategy when storage/space issue becomes important.

I think what i will also do is to add a flag to each record where a purge can occur to add clarity that a column value has been purged rather than missing data.

Yes, adding such a column is a good idea. You may also want to include a timestamp as well.