Row Normalizer

Description

The Row Normalizer step normalizes data back from pivoted tables. For example, below is a sample table of product sales data:

Month	Product A	Product B	Product C
2003/01	10	5	17
2003/02	12	7	19
...	...	...	...

The Row Normalizer step converts the data into the format below
so that it is easier to update your fact table:

The following options are available for the Row Normalizer Step:

Option	Description
Step name	Name of the step; this name has to be unique in a single transformation.
Typefield	The name of the type field (product in the example above)
Fields table	A list of the fields you want to normalize; you must set the following properties for each selected field: Fieldname: Name of the fields to normalize (Product A ? C in the example). Type: Give a string to classify the field (A, B or C in our example). New field: You can give one or more fields where the new value should transferred to (sales in our example).
Get Fields	Click to retrieve a list of all fields coming in on the stream(s).

The example below illustrates using the Row Normalizer step to normalize more than one row at a time starting with the following data format:

DATE	PR1_NR	PR_SL	PR2_NR	PR2_SL	PR3_NR	PR3_SL
20030101	5	100	10	250	4	150
...	...	...	...	...	...	...

You can convert the data to a table similar to the one shown below:

DATE	Type	Product Sales	Product Number
20030101	Product1	100	5
20030101	Product2	250	10
20030101	Product3	150	4
...	...	...	...

Below is the setup you use to create the table: