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Transforming Customer Data From AWS S3 to Data Cloud

Transforming Customer Data From AWS S3 to Data Cloud

In today’s digital age, efficiently managing customer data is crucial for businesses. With the increasing complexity of customer information, having a streamlined process for organizing and accessing data is essential. 

This article will explore how to transform contact information from AWS S3 to enable the storage of multiple identifiers per customer in a custom Identifier List Data Lake Object (DLO). By implementing these strategies, you can ensure your customer data is well-organized and easily accessible within your data cloud, enhancing your overall data management capabilities.

Starting the Data Transformation Process

First, click on Data Transforms and then select New. Choose Batch Data Transforms and click Next. Select Data Lake Objects and click Next again to open a new tab.

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Adding Input Data

Add input data from AWS S3 customers, but only include three fields:

  1. Customer Reward Number (Number)
  2. Customer ID (Text)
  3. Passport Number (Text)

Click Next to proceed.

Filtering Records with Passport Numbers

  1. Click the Plus icon and use filters to extract records with passport numbers.
  2. Name the filter transformation Get Passport Number, and click Apply.
  3. Use the Add Custom Expression with the function `char length` to get the length of the passport number field.
  4. Set the condition to extract records where the passport number length is greater than zero.
  5. Click Apply.

Adding and Transforming Columns

  1. Click the Plus icon and select Transform.
  2. Name this step Add Key, Identifier Type and Name, and Drop Column.
  3. First, drop the Customer Reward Number column. Select this column and click Drop Column.
  4. Name this transformation, Drop the Customer Reward Number, and click Apply.
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Adding Key Identifier

  1. Add a key using a custom formula with the concatenation function.
  2. Name this transformation Add Key.
  3. Use the `Concat` function with Customer ID as the first field and Passport Number as the second field.
  4. Set the output as text and name the column Identifier Key.
  5. Set the API name as `Identifier_Key__c` and click Apply.
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Adding Identifier Name

  1. Add a column for the identifier name using a custom formula.
  2. Name this transformation Add the Identifier Name and hard-code the value to the Passport Number.
  3. Set the output as text and label the column Identifier Name.
  4. Set the API name as `Identifier_Name__c` and click Apply.

Adding Identifier Type

  1. Add a column for the identifier type using a custom formula.
  2. Name this transformation, Add Identifier Type, and hard-code the value to Identifier.
  3. Set the output as text and label the column Identifier Type.
  4. Set the API name as `Identifier_Type__c` and click Apply.
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 Also Read: How To Import Customer & Order Data to Salesforce Data Cloud From AWS S3

Renaming the Passport Number Column

  1. Rename the Passport Number column to Identifier Number.
  2. Select Passport Number, use Edit Attributes, and name this transformation Rename to Identifier Number.
  3. Set the new label to Identifier Number and the API name to `Identifier_Number__c`.
  4. Click Apply.
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With these transformations, the output will include:

  • Customer ID
  • Identifier Number
  • Identifier Key
  • Identifier Name
  • Identifier Type
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Loading Data into the Identifier List DLO

  1. Click the Plus icon and select Output.
  2. Choose the Identifier List Data Lake Object.
  3. Map the fields as follows:
  • Customer ID to Party
  • Identifier Number to Identification Number
  • Identifier Key to Identifier Key
  • Identifier Name to Identification Name
  • Identifier Type to Party Identification Type
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  1. Click Apply and save the transformation as Extract Identifiers from AWS S3 Customers.

Handling Records with Customer Reward Numbers

Next, repeat the steps for records with customer reward numbers with a few changes:

  1. Convert Customer Reward Number from number to text.
  2. Select Customer Reward Number, use Number to Text, and name this transformation Convert to Text.
  3. Display the results in the existing column and click Apply.
  4. Use a filter to get records with a Customer Reward Number greater than zero.
  5. Use Char Length with the field Customer Reward Number and set it to greater than zero.
  6. Click Apply.

Add and transform columns similarly to the previous steps:

  1. Drop the Passport Number column.
  2. Concatenate Customer ID and Customer Reward Number to create an Identifier Key.
  3. Hard-code Identifier Name to Customer Reward Number.
  4. Hard-code Identifier Type to Identifier.
  5. Rename Customer Reward Number to Identifier Number.
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Combining Transformations

  1. Append the output of this transformation to the output of the previous one.
  2. Select Append and ensure the keys are correctly matched based on column names.
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Finally, save the transformation and review the output, which will now include customers with both their passport and reward numbers as identifiers.

Explore our Salesforce Data Cloud series on YouTube for expert guidance and tips on leveraging Salesforce Data Cloud effectively.

Conclusion

Efficiently managing and transforming customer data from AWS S3 into custom Identifier List Data Lake Objects is essential for businesses aiming to optimize their data management processes. By following the steps outlined in this guide, you can ensure that your customer data is not only well-organized but also easily retrievable and usable within your data cloud. This approach will enhance your ability to handle multiple identifiers per customer, ultimately improving your overall data management strategy.

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