# Does it make sense to apply clustering on aggregation of data?

I was wondering if it makes sense to apply clustering techniques on an aggregation of data, like, I have three different sources of data such as S1 S2 and S3 where each of these sources share some common columns but the majority are not shared. Does it make sense to group all the sources with all the columns in a big dataframe and apply clustering techniques whereas some records will only have null values for the columns that are not part of its corresponding service. Thank you.

Update: The input is basically logs coming from different services with different columns where some of them are shared between all services. The output should be a cluster of records representing a user having the same behavior.
The logs are gathered by second corresponding of a user action. They are aggregated by hours for each user to derive other features (the granularity of seconds it according to me, too much).
The goal, is to detect anormal behaviors.
And the question is, can I regroup different dataframe having different features while some of them are shared and run a K-mean on it. Because my dataframe would look like this (s* for service, and common_ for common feature):

-------------------------------------------------------------
s1_f1 | s1_f2 | s2_f1 | s2_f2 | s3_f1 | common_f1 | common_f2
1       OK     NULL    NULL    NULL     midday      less
2       OK     NULL    NULL    NULL     midnight    more
NULL    NULL     2       5      NULL     midday      less
NULL    NULL     8       9      NULL     morning     less
NULL    NULL    NULL    NULL    777      morning     more
NULL    NULL    NULL    NULL    888      night       more

• What would be the output, and how sould you put it into use? There is no use in just doing something without a plan. Apr 13 '16 at 21:09
• @marcL, You mentioned data "aggregated", which implies some type of summarization -- or roll-up -- of the data. However, based on the details you've provided, it appears that you're just stacking three data sets that came from different sources. Can you clarify? Apr 13 '16 at 21:31
• @Vishal I updated my question, hope its more clear now Apr 14 '16 at 21:46