# EXAMPLE - PREV Function

This example describes how you can use the PREV function to analyze data that is available in a window in rows before the current one.

Functions:

Item

Description

PREV Function

Extracts the value from a column that is a specified number of rows before the current value.

IF Function

TheIFfunction allows you to build if/then/else conditional logic within your transforms.

The following dataset contains orders for multiple customers over a period of a few days, listed in no particular order. You want to assess how order size has changed for each customer over time and to provide offers to your customers based on changes in order volume.

Source:

Date

CustId

OrderId

OrderValue

1/4/16

C001

Ord002

500

1/11/16

C003

Ord005

200

1/20/16

C002

Ord007

300

1/21/16

C003

Ord008

400

1/4/16

C001

Ord001

100

1/7/16

C002

Ord003

600

1/8/16

C003

Ord004

700

1/21/16

C002

Ord009

200

1/15/16

C001

Ord006

900

Transformation:

When the data is loaded into the Transformer page, you can use the PREV function to gather the order values for the previous two orders into a new column. The trick is to order the window transform by the date and group it by customer:

 Transformation Name Window PREV(OrderValue, 1) CustId Date
 Transformation Name Window PREV(OrderValue, 2) CustId Date
 Transformation Name Rename columns Manual rename window 'OrderValue_1'
 Transformation Name Rename columns Manual rename window1 'OrderValue_2'

You should now have the following columns in your dataset: Date, CustId, OrderId, OrderValue, OrderValue_1, OrderValue_2.

The two new columns represent the previous order and the order before that, respectively. Now, each row contains the current order (OrderValue) as well as the previous orders. Now, you want to take the following customer actions:

• If the current order is more than 20% greater than the sum of the two previous orders, send a rebate.

• If the current order is less than 90% of the sum of the two previous orders, send a coupon.

• Otherwise, send a holiday card.

To address the first one, you might add the following, which uses the IF function to test the value of the current order compared to the previous ones:

 Transformation Name New formula Single row formula IF(OrderValue >= (1.2 * (OrderValue_1 + OrderValue_2)), 'send rebate', 'no action') 'CustomerAction'

You can now see which customers are due a rebate. Now, edit the above and replace it with the following, which addresses the second condition. If neither condition is valid, then the result is send holiday card.

 Transformation Name New formula Single row formula IF(OrderValue >= (1.2 * (OrderValue_1 + OrderValue_2)), 'send rebate', IF(OrderValue <= (1.2 * (OrderValue_1 + OrderValue_2)), 'send coupon', 'send holiday card')) 'CustomerAction'

Results:

After you delete the OrderValue_1 and OrderValue_2 columns, your dataset should look like the following. Since the transformations with PREV functions grouped by CustId, the order of records has changed.

Date

CustId

OrderId

OrderValue

CustomerAction

1/4/16

C001

Ord001

100

send rebate

1/7/16

C001

Ord002

500

send rebate

1/15/16

C001

Ord006

900

send rebate

1/8/16

C003

Ord004

700

send rebate

1/11/16

C003

Ord005

200

send rebate

1/21/16

C003

Ord008

400

send coupon

1/7/16

C002

Ord003

600

send rebate

1/20/16

C002

Ord007

300

send rebate

1/21/16

C002

Ord009

200

send coupon