OmniStudio Data Mapper is a powerful tool. They play a vital role in connecting your applications with Salesforce by seamlessly delivering data from the database to components like Cards, Integration Procedures, and OmniScripts.
This blog will show you how to use OmniStudio Data Mappers and their different types to read, write, transform, calculate, and manage data in your Salesforce org.
What is Data Mapper in Salesforce?
You need to get, change, or save data during a customer interaction or business process. That’s where Salesforce OmniStudio Data Mappers come in.
An OmniStudio Data Mapper is a mapping tool. You can read, modify, and write Salesforce data directly using this tool. It’s remarkably efficient at managing the flow of your data.
How Data Mappers Work
Here’s a simple breakdown of the data flow:
Get Data: An OmniScript tells a DataMapper Extract (often through an Integration Procedure) to pull data from Salesforce. For instance, an OmniScript “Edit Account” must show details like the account name, website, and phone number.
Manipulate Data: Any changes or new data you enter are recorded by OmniScript. For example, when you change the phone number associated with an account.
Save Data: The OmniScript then tells a Data Mapper Load (again, often through an Integration Procedure) to write that data back to Salesforce. This updates the account record with the new phone number.
DataMapeers: Powerful Code Capabilities in Salesforce
Need to work with data in Salesforce? DataMappers make it easy. They offer powerful “code capabilities” that make these tasks much simpler and more efficient.
ETL for Salesforce
DataMapeers act as an ETL (Extract, Transform, Load) tool specifically for Salesforce. Their mapping capabilities allow you to read, write, and transform JSON and XML inputs. You can even transform data without having to read it from or write it to Salesforce first.
Declarative No-Code/Low-Code
One of the best things about DataMapeers? They are declarative. This means you don’t write code to pull data from Salesforce. It’s truly a no-code or low-code solution!
Substitute for Apex
While Apex classes can certainly read, write, and transform data, they generally take longer to create and are harder to maintain than DataMappers. That’s why using Data Mappers is a best practice if you’re working with OmniStudio (formerly Vlocity).
Handle Custom Data Formats
DataMappers Extract and Load types are super flexible. They can handle custom data formats and even access external objects and custom metadata, as well as sObjects.
Types of OmniStudio DataMapper
Data Mapper Extract
When you need to read and pull data from Salesforce, you use a Data Mapper Extract. This tool takes information from Salesforce and gives it to you in JSON, XML, or other custom formats.
Data Mapper Extracts give you lots of options. You can filter the data and choose the specific fields you want to return. This type of DataMapper also supports formulas, default values, and translations. It allows you greater control over the data you extract.
Ultimately, these extracts provide the necessary data to other OmniStudio components like OmniScripts, Integration Procedures, and FlexCards. It makes them a vital part of your application.
DataMapper Turbo Extract
When you need to grab data fast from Salesforce, the DataMapper Turbo Extract is your friend. It efficiently retrieves information from just one Salesforce object type, and it can even include fields from related objects.
You can filter your data and choose specific fields to return. Turbo Extracts are simpler to set up and run faster because they focus on just one object.
But, they have a few limits. A Turbo Extract doesn’t use formulas, and because it doesn’t have an “Output” tab, you can’t arrange the data with special mappings. It also doesn’t support custom JSON, default values, or translations.
While it does have a Preview Tab, it works differently from a regular DataMapper Extract. Still, its simple approach makes it super effective for getting data quickly.
Data Mapper Load
Data Mapper Load accepts data in various formats, including JSON, XML, or custom input formats, and then writes this information directly to your Salesforce objects.
You can also use formulas and attributes with your data. This means you can change or add to the information as it goes into Salesforce. For example, when someone finishes filling out an OmniScript for a case and clicks “Save,” Data Mapper Load quickly records all that new data. It’s a straightforward way to manage your Salesforce data.
Data Mapper Transform
Need to change your data around without touching Salesforce? Data Mapper Transform is your tool. This powerful tool lets you make intermediate transformations to your data, and you can even add formulas to get it just right.
Data Mapper Transform handles several key tasks:
- Convert Data Formats: Easily change your data from JSON to XML, or back again.
- Restructure and Rename: Reorganize your data and change field names to whatever you need.
- Substitute Values: Quickly replace values in fields. A feature all Data Mappers support.
- Generate Documents: It can turn your data into things like PDFs, DocuSign files, or Document Templates.
Looking to get expertise in OmniStudio DataMapper? Enrol in our Salesforce OmniStudio Consultant training course.
Common DataMapper Mistakes
DataMappers help you manage data in Salesforce, but people often make similar mistakes that can slow things down. Watch out for these common issues to keep your DataMappers working their best.
- Many teams don’t set the VlocityMetadata Platform Cache.
- Teams often add many objects to their DataMappers when they could simply use relationship queries to get related data more efficiently.
- Some teams try to build a single “Uber” DataMapper to handle all their data needs, sometimes connecting to as many as 12 objects.
- Your DataMapper might pull in more data than it actually needs. This wastes resources and can slow down your processes.
- DataMappers can use formulas, but many teams use too many—sometimes as high as 30.
DataMapper Best Practices
|
Best Practice |
Description |
|
Name Things Clearly |
Always use unique names for OmniScript parts and Data Mapper results. This prevents confusion and keeps your projects organized. |
|
Focus Your Data Mappers |
Build Data Mappers to do just one specific job. They should only get or put in the data you need for that single task. |
|
Use Relationship Queries |
When you need data from connected Salesforce objects, use relationship queries. This pulls related information efficiently and means you don’t need multiple steps to get data. |
|
Limit Salesforce Objects |
To avoid slow performance, keep the number of Salesforce objects you access to three or fewer. |
|
Index Your Filters and Sorts |
Make sure that any fields you use to filter or sort data have indexes. Salesforce always indexes Id and Name fields. If you filter or sort by other fields, check that they also have indexes. |
|
Use Caching |
Store data you access often but don’t update frequently in the cache. This decreases the number of repetitive database queries and speeds up data retrieval. |
|
Check Encrypted Data Permissions |
Before you show or use any decrypted data from encrypted fields, always confirm the user has the View Encrypted Data permission. This protects your sensitive information. |
Also read: How to maximise efficiency with Salesforce OmniStudio?
Naming Your DataMappers Effectively
Giving your DataMappers clear, consistent names is crucial for an organized and efficient Salesforce environment. Well-named DataMappers are easy to find, understand, and manage, especially as your projects grow.
Here are the key points for naming your DataMappers:
- Unique Names, No Spaces: Each DataMapper name must be unique within your Salesforce organization, and it can’t have any spaces.
- Use CamelCase: We recommend using camelCase for readability.
- Follow a Pattern: A good pattern to follow is prefixVerbObjectDetail. This helps you quickly understand what the DataMapper does.
- Action Verbs and Descriptive Nouns: Use an action verb (like “get” or “create”) with descriptive nouns (like “account” or “cases”).
- Use Abbreviations: Feel free to use abbreviations when they make sense, and keep the name concise.
- Example: A good example following this convention is teamGetAcctCases. This immediately tells you that a “team” is “getting” “account cases.”
Conclusion: Master Your Data with OmniStudio Data Mappers
Salesforce OmniStudio Data Mappers are essential for anyone who wants to improve how data moves and is managed in Salesforce. These strong, straightforward tools help you extract, load, and change data much more efficiently than traditional coding. This makes complex data work easy for everyone.
Data Mappers come in different types. By understanding these types and following best practices, you can avoid common problems. This will greatly boost how well your Salesforce apps perform and how easy they are to maintain.
Mastering OmniStudio Data Mappers isn’t just about moving data. It’s about unlocking your Salesforce org’s full potential and building strong, flexible solutions. Are you ready to advance your OmniStudio skills?
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