Sync Salesforce Marketing Cloud Data to Azure Synapse Analytics in Minutes
Salesforce is a software company offering cloud-based solutions for businesses that want to prioritize customer experiences throughout every stage of the customer journey. With tools for finding prospects, closing deals, and supporting customers with incredible service, Salesforce makes it easy to build a brand with a 360-degree view of your customers.
Azure Synapse Analytics is a scalable cloud-data warehouse that integrates data analytics, machine learning, and advanced business intelligence for all of your data within.
Extract data from and load data into Salesforce to create your Customer 360 view.
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Connect Salesforce Marketing Cloud to Azure Synapse Analytics and 200+ other platforms in minutes.
Talk to an expertFAQ
Clear answers to the questions teams ask when evaluating Integrate.io.
Still have questions?
Talk to an expert →Yes. Integrate.io helps teams build managed pipelines that move Salesforce Marketing Cloud data into Azure Synapse Analytics for analytics, operations, and reporting workflows.
The available Salesforce Marketing Cloud data depends on the connector, authentication, API permissions, and objects selected. Integrate.io helps map that data into Azure Synapse Analytics fields and tables.
Yes. Integrate.io supports mapping, filtering, joins, enrichment, scheduling, monitoring, and error handling before Salesforce Marketing Cloud data reaches Azure Synapse Analytics.
Refresh timing depends on source limits, destination capacity, data volume, and business requirements. Teams can configure schedules that keep Azure Synapse Analytics updated from Salesforce Marketing Cloud.
Most Salesforce Marketing Cloud to Azure Synapse Analytics pipelines can be configured visually in Integrate.io. Teams can add advanced logic when the integration requires API-specific handling or custom transformations.
Start with a scoped Salesforce Marketing Cloud sync, confirm field mapping and row counts in Azure Synapse Analytics, review pipeline logs, then schedule the production workflow once the data matches expectations.
