This transformation pivots data from multiple rows into columns in a single row.
- Columns to Group By - a comma-separated list of columns to group by. This parameter is a required field for the transformation.
- Columns to Include - a comma-separated list of columns to include. For example:
phoneare specified as the only columns to include. Then,
agewill be included in the final dataset.
- Columns to Exclude - a comma-separated list of columns to exclude. For example:
ssnare specified as columns to exclude. Then,
agewill not be included in the final dataset.
- Leading Column - the name of the leading column. The leading column sets the pattern for the other columns. For example, if the
Addressis a leading column, and there are
2addresses for the given first+last name, but there are
4phones, the phones will be included in the final dataset
2times as well.
- Max # of Columns - the maximum number of columns permitted. Use this parameter to set a limit on how many times denormalized columns can be repeated. For example, if there are
4addresses for the given first+last name, and the limit is set to
address2will be included in the final dataset.
Columns to Group By set to
id,address,phone 1,main stree1,412111111 1,anderson dr,412111112 2,home, 3,home,home phone 3,work,work phone 3,,mobile phone
id,address,address_2,address_3,phone,phone_2,phone_3 1,main stree1,anderson dr,,412111111,412111112, 2,home,,,,, 3,home,work,,home phone,work phone,mobile phone
To configure Denormalize transformation go to Transformation/MAPPING/Complex Transformations/Denormalize Dataset.