Once you’ve successfully connected Salesforce to Nexadata, you can begin using the connection to either bring Salesforce data into Nexadata (Datasets) or send transformed data back to Salesforce (Pipeline Outputs). This article will walk you through each option step by step.
Here are the key capabilities:
Import data from Salesforce using SOQL queries or prebuilt Salesforce Reports
Export transformed data back to Salesforce with support for Insert, Update, Upsert, or Delete actions
Dynamically configure the Salesforce Object, Properties, and Field mappings based on your CRM schema
Validate schema and field mappings to ensure alignment between Nexadata datasets and Salesforce targets
Optimize syncs with Real-time or High-volume modes for maximum flexibility
Part 1: Creating a Dataset from Salesforce via SOQL
Use this option if you need granular control over the data you pull from Salesforce.
Step 1: Create a New Dataset
Navigate to the Datasets section in Nexadata.
Click Create Dataset.
Under Data Connection, select your configured Salesforce connection.
Step 2: Configure Dataset Properties
Name: Provide a unique name for the dataset.
Data Connection: Confirm your existing Salesforce connection is selected.
Data Format: Choose from:
Tabular – Recommended for most Salesforce CRM data.
JSON or Parquet – Use if your pipeline requires these formats.
Step 3: Build Your SOQL Query
Select Salesforce Object Query Language (SOQL) as the query type.
Choose an Object (e.g., Contact, Account, Opportunity).
Select the Properties (fields) you want to extract and see that your SOQL query gets automatically built.
Optionally, use the SOQL Query editor to customize your query further. Example:
SELECT Id, FirstName, LastName, Email, AccountId FROM Contact
Additional options:
Include soft delete – Choose whether to include records marked as deleted in Salesforce.
Extract mode – Select Real-time or High-volume depending on your use case.
Record Batch Size – Define how many rows to pull in each request (default: 2000).
Step 4: Submit the Dataset
Review your dataset configuration.
Click Submit to save.
The dataset is now ready for use in Nexadata pipelines.
Part 2: Creating a Dataset from Salesforce via a Salesforce Report
Use this option if you want to pull data from predefined Salesforce Reports that already aggregate and filter your CRM data.
Step 1: Create a New Dataset
Navigate to the Datasets section in Nexadata.
Click Create Dataset.
Under Data Connection, select your configured Salesforce connection.
Step 2: Configure Dataset Properties
Name: Provide a unique name for the dataset.
Data Connection: Confirm your existing Salesforce connection is selected.
Data Format: Choose Tabular (recommended).
Step 3: Select Report
Choose Salesforce Report as the query type.
Use the dropdown to select a report (e.g., Leads by Status).
Enable Auto Detect Delimiter if needed for parsing fields.
Step 4: Submit the Dataset
Review the dataset configuration.
Click Submit to save.
Your Salesforce Report dataset is now ready for pipelines.
Part 3: Sending Data Back to Salesforce
After transforming data in a Nexadata pipeline, you can send the results back to Salesforce using the Output Builder.
Step 1: Select a Connection and Object
Choose your configured Salesforce Connection.
Select the Salesforce Object (e.g., Contact, Account).
Step 2: Choose an Action
You can control how Nexadata writes data back into Salesforce:
Insert – Create new records.
Update – Update existing records only.
Upsert – Update existing records, or create new ones if no match is found.
Delete – Remove records in Salesforce.
Step 3: Map Columns to Salesforce Properties
For each column in your pipeline output:
Select the Column from Nexadata.
Map it to the corresponding Salesforce Property (e.g., First Name, Last Name, Phone).
This ensures your data aligns with Salesforce’s schema.
Step 4: Save and Run
Once all mappings and actions are configured, click Start Transforming.
Nexadata will process your dataset and push results back to Salesforce according to the defined rules.
Tips and Best Practices
Use Upsert for flexibility – It handles both new records and updates in a single sync.
Check required fields – Ensure Salesforce-required fields (e.g., Email for Contacts) are mapped to avoid sync errors.
Optimize batch size – Larger batch sizes speed up high-volume exports but may increase API rate usage.
Test in Sandbox first – Use the Test environment before deploying changes to Production.
Leverage SOQL – For complex filtering, joins, or custom fields, use the Customize SOQL option to add in your own parameters.