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Field mappings are at the heart of any data integration. They control how data moves from one system to another and what happens to it along the way. Rapidi gives you a set of built-in formulas that let you convert, filter, look up, and transform your data without writing custom code.
This guide covers best practices for both platforms and shows you, step by step, how to set up your field mappings in MyRapidi.
In the 5th Session of our Open Office Hours series, we will explain how to set up Field Mappings via Rapidi.
In this Open Office Hours session, we walk through how to use formulas in Rapidi's field mappings for situations where a simple 1-to-1 mapping isn't enough.
Topics covered include:
We also share practical tips: start with simple formulas, test them, then add complexity through nesting as needed. The full formula reference is available on the Rapidi wiki.
Watch the Replay of our fifth session: Field Mappings
Field mappings can be simple 1-to-1 relationships between a source field and a destination field. In many integrations, that approach is not enough because data may need to be pulled from different places, reformatted, validated, shortened, or mapped conditionally. RAPID formulas (also called expressions) cover these cases.
Formulas are added in Field List Mappings.
##'text'"FieldName"This structure applies to formulas and to hardcoded values.
RAPID formulas are grouped into categories that match common mapping needs.
Conversions handle cases where two systems store the same data in different formats. The goal is to align formats so the destination receives the expected structure.
A common example is converting a date from the source into a date-and-time format required by the destination.
Conditional logic is used when:
A common scenario is mapping values that do not match between systems.
Example pattern:
east, west, northeast → 1west → 2north → 3The default is placed at the end to ensure the transfer runs correctly.
A blank value formula is often paired with lookups:
Example behavior:
Lookups retrieve data from other tables, lists, or views and send it to the destination.
A lookup requires something in common between:
Example structure (destination lookup):
DDS is used for lookups against the destinationSourceDS is used for lookups against the sourceLS lookup is used for link storage values, which must be kept up to date to be reliableText manipulation formulas adjust strings to match destination constraints.
A common use is preventing destination errors caused by long strings.
Example:
name allows up to 50 charactersHardcoded values follow the same syntax rules:
##Hardcoding is used to always send consistent values or to provide defaults.
The message formula logs selected field values during transfer runs.
Example behavior:
The error formula stops a transfer from running. It is used when a strict validation is required, and missing or invalid data must block processing.
Validation formulas can check field formats before sending data:
## prefix, single quotes for strings, double quotes for field namesRAPID field mappings support more than 1-to-1 field transfers. Formulas enable format conversions, conditional mapping with defaults, lookups across source/destination/link storage, text length control, validation, logging, and hard-stop error handling. Correct syntax and incremental build-up of logic reduce mapping errors and improve transfer reliability.
Session covers timestamps and RTI, formulas, and transformations. Learn how to configure how your data moves between systems.
Can't attend live? Register anyway, and we'll send you the recording and materials afterward.
Field mapping is the process of connecting a field in one system to a corresponding field in another. It tells the integration which data goes where. A simple example: the "Customer Name" field in your ERP needs to map to the "Account Name" field in Salesforce. Without correct mapping, data ends up in the wrong place or doesn't transfer at all.
A 1-to-1 mapping sends a value directly from a source field to a destination field without any changes. A formula-based mapping transforms the data along the way. You'd use a formula when the two systems store data in different formats, use different values for the same thing, or when you need to pull data from a related table that isn't part of the main transfer.
If you don't account for blank fields, your transfer may either fail or push empty values into the destination, which can overwrite existing data. In Rapidi, you can use a Blank Value formula combined with Skip Field to tell the system: "If this field is empty, leave the destination field as it is." This is especially useful for fields that aren't always filled in by end users.
Systems often define the same kind of data differently. A name field might allow 50 characters in your ERP, but only 30 in Salesforce. A date field might use one format (DD/MM/YYYY) in one system and another (YYYY-MM-DD) in the other. These mismatches cause validation errors on the receiving end. Rapidi's COPY and FORMAT formulas let you trim field lengths and convert formats before data reaches the destination.
Use a lookup when the data you need isn't available on the table you're transferring. For example, if you're syncing customer records but need to include the outstanding invoice amount, that value might live in a separate statistics table. A lookup lets you query another table, match on a shared identifier (such as a customer number), and pull the value into your transfer. In Rapidi, you can run lookups on the source system, the destination system, or the link storage.
Andreea Arseni, Senior Data Integration Consultant
Open Office Hours Season 1: Session 5 - Field Mappings
Open Office Hours Season 1: Session 4 - Connections: ...
Open Office Hours Season 1: Session 3 - Connections: D365 ...
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