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Mappings in advanced mode example

You work for a retail company that offers more than 50,000 products and the stores are distributed across the globe. The company ingests a large amount of customer engagement details from the transactional CRM system into Amazon S3.

The sales team wants to improve customer engagement and satisfaction at every touch point. To create a seamless customer experience and deliver personalized service across the various outlets, the retail company plans to load the data that is stored in the parquet file format from the Amazon S3 bucket to Snowflake.

You can create a mapping in advanced mode to read data from the Amazon S3 bucket and write data to the Snowflake target. You can choose to add transformations in the mapping to process the raw data that you read from the Amazon S3 bucket and then write the curated data to Snowflake.

The following example illustrates how to create a mapping to read from an Amazon S3 source and write to Snowflake:

The mapping includes an Amazon S3 source, Expression transformation, and Snowflake target.

In Data Integration, click

New

Mappings

Mapping

In the Mapping Designer, click

Switch to Advanced

The following image shows the

Switch to Advanced

button in the Mapping Designer:

In the

Switch to Advanced

dialog box, click

Switch to Advanced

The Mapping Designer updates the mapping canvas to display the transformations and functions that are available in advanced mode.

Enter a name, location, and description for the mapping.

Add a Source transformation, and specify a name and description in the general properties.

On the

Source

tab, perform the following steps to read data from the Amazon S3 source:

In the

Connection

field, select the Amazon S3 V2 connection.

In the

Source Type

field, select single object as the source type.

In the

Object

field, select the parquet file object that contains the customer details.

In the

Advanced Properties

section, specify the required parameters.

The following image shows the configured Source transformation properties that reads customer engagement details from the Amazon S3 object:

You can view the Amazon S3 source configured properties.

On the

Expression

tab, define an expression to change the file name port of the customer parquet file to uppercase based on your business requirement before you write data to the Snowflake target:

The following image shows the configured Expression transformation properties: