Explore Data Mapper Integration Within Omnistudio

Learning Objectives

After completing this unit, you’ll be able to:

Explain how Omniscripts use Data Mappers to get, modify, and load data.
Describe how Integration Procedures work as an orchestration layer for Data Mappers.
Explain how Flexcards consume data provided by Data Mappers.

Use Data Mappers with Other Omnistudio Components

As you’ve learned throughout this module, Omnistudio Data Mappers are used by other Omnistudio components to provide, transform, and write data. In this unit, you learn how Omniscripts, Integration Procedures, and Flexcards consume data from Data Mappers to provide streamlined experiences for your users and customers.

As a brief overview, here’s how Data Mappers work with every other Omnistudio component.

Omniscripts use Data Mappers to retrieve and save data within user interactions.
Integration Procedures can include multiple Data Mappers that retrieve and save data.
Flexcards display data retrieved by Data Mappers.

Let’s go deeper into how each component works with Data Mappers, starting with Omniscript.

Explore Data Mapper Usage in Omniscripts

Omniscript helps you efficiently design guided interactions for fast, personalized, and consistent experiences. It’s your go-to tool for building guided processes used inside and outside your company when custom design and advanced data operations are important.

Omniscripts handle the user interaction and use Data Mappers for retrieval, manipulation, and saving of Salesforce data.

Data Mappers are often used by an Omniscript to get the data shown to the user or drive process logic. In an Omniscript, an Omnistudio Data Mapper Extract or Data Mapper Turbo Extract finds Salesforce objects using information from the Omniscript, such as a record ID or search term. It returns the data to the Omniscript’s Data JSON. This helps ‌Omniscript dynamically load and show information relevant to the user in a process step.

After a user interacts with an Omniscript and updates or enters information, a Data Mapper Load saves that data to Salesforce. Omniscript uses its Data Mapper Post Action element to send the collected data to a configured Data Mapper Load. The Data Mapper Load then creates or updates Salesforce records from the data received from the Omniscript.

Beyond just reading and writing data, Omniscripts transform or restructure data during a process using a Data Mapper Transform. A Data Mapper Transform can change the Omniscript’s Data JSON without directly querying Salesforce records. This is especially useful for changing data before sending it to a different service, like filling in a DocuSign or PDF template.

Check out this screenshot of a sample Omniscript in the Omniscript Designer.

Two Data Mapper actions highlighted in Omniscript Builder.

The Omniscript uses a Data Mapper Extract Action to get data, then later a Data Mapper Transform Action to modify it.

Investigate Data Mapper Usage in Integration Procedures

In the last unit, you learned that Integration Procedures are powerful tools for orchestrating complex back-end logic. They can process many steps in sequence, branch conditionally, call external services, and work with data from Salesforce and beyond.

Among the many actions you can configure, Integration Procedures often include Data Mappers to retrieve, manipulate, and load Salesforce data. Data Mappers work within an Integration Procedure to handle data at key points in the process. For example, an Integration Procedure can call a Data Mapper Extract or a Data Mapper Turbo Extract to read data from Salesforce and return it to the procedure’s Data JSON. That data can then be used by other steps and returned in the final response.

Integration Procedures also use Data Mappers to write data to Salesforce after it’s been processed or collected. A Data Mapper Load can use the Integration Procedure’s data JSON to create or update records. A Data Mapper Load can also create JSON outputs for later steps within an Integration Procedure.

Integration Procedures, with their ability to orchestrate actions in a specific order, are also the perfect place to restructure data with Data Mapper Transforms. Data Mapper Transforms can perform significant restructuring or manipulation before being used in later Integration Procedure actions, such as sending data to an external system or preparing it for a final response.

You can use Integration Procedures to package multiple Data Mappers into a reusable flow. For example, instead of configuring Extract, Transform, and Load actions directly in each Omniscript, you might call an Integration Procedure that performs all of those steps by sequencing Data Mappers. This approach keeps Omniscripts focused on user interaction, promotes reuse across Omnistudio projects, and improves performance by centralizing configuration.

That’s not all. Integration Procedures enhance the performance of Data Mappers by pairing them with other actions. For example, if you want to extract data from a Salesforce object and then group or manipulate the list based on some criteria, extract the full list and perform the manipulation using a List Action in an Integration Procedure.

Take a look at this screenshot of an Integration Procedure in the Integration Procedure Designer. It uses two Data Mapper Extract Actions to get data from two different Data Mappers, then returns all of the data.

Two Data Mapper Extract Actions highlighted in an Integration Procedure.

Review Data Mapper Usage in Flexcards

Flexcards are designed to provide rich, dynamic user interfaces with contextual information and actions, often needing to interact with data efficiently.

Data Mappers can get the data that Flexcards show using a Data Mapper Extract or Data Mapper Turbo Extract. This helps the Flexcard get data from Salesforce objects and populate the card with dynamic content. Using Data Mappers this way also offers the benefit of automatically applying Salesforce field-level security.

To make sure the data displayed on a Flexcard is relevant to the user’s current context, Flexcards pass information to the Data Mapper to determine what data to return. For instance, a Flexcard on a record page can pass the record’s ID using a variable as an input parameter to a Data Mapper Extract. The Data Mapper Extract uses the record ID to query and return data related to that record, such as cases based on an account ID.

Here’s a sample Flexcard in the Flexcard Designer.

The Datasource panel setup is highlighted with the Data Source Types value or Data Mapper.

This example uses a Data Mapper in the Datasource section of Setup. It includes a way to map key-value pairs from the Data Mappers, and also enter test key-value pairs.

Wrap Up

In this module, you learned the fundamentals of Omnistudio Data Mappers, which are essential tools for reading, transforming, and writing data within Salesforce.

Let’s do a quick recap. You explored the four distinct types of Data Mappers.

Turbo Extract for simple, single-object data retrieval
Extract for more complex retrievals with filters and data formatting
Transform for manipulating data without direct Salesforce interaction
Load for updating or creating records in Salesforce

You learned the basics of how to create and set up Data Mappers: You explored some essential best practices for maximizing performance and reusability, leading to more efficient and maintainable solutions.

And you learned that Omnistudio Data Mappers are important to other Omnistudio components, like Omniscripts, Integration Procedures, and Flexcards. You now know more about Omnistudio tools and their collective power in building comprehensive solutions.

As you wrap up this module, take a moment to consider how you can apply these concepts within your own organization. How can you use Data Mappers to streamline data processes, enhance user experiences, and improve efficiency? Think about specific challenges your team faces, and then explore how the flexibility and power of Data Mappers can provide solutions.

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