Pre-processing Data - Best Practices

Hi,

I am a relatively new user to KNIME and I am trying to evaulate whether our statistical analytics team should begin to use KNIME.

I was wondering what the best practices for generating new columns based on indicators are.  Example below:

ClaimID,Gender,Age,State,Allowed Amt,Billed Amount
1,F,60,MN,10455,
2,M,13,TX,4651
3,F,94,FL,10679
4,F,76,NY,1856
5,M,26,MN,3968

Given this type of data.  I want to produce indicator fields to produce a vector such as:

Female,Male,Age_0_15,Age_15_30,Age_30_45,Age_45+,MN/TX,NY/FL,Amount_Over_5K
0,1,0,1,0,0,1,0,1
1,0,1,0,0,0,0,1,0

The way that I am producing the above is rather round-about.  I am using the One-2-Many node to produce Male/Female indicators. 

I am binning the state/age/amount and then using One to many.

Is there any easier way or is this appropriate?

Regards,

SC

I think this task can be easily solved by using the Binner and the Bitvector Generator node. Hope it helps.