From identifying targets with proprietary market data to closing on time and separating cleanly in a divestiture — having all of your data in one place can make or break your M&A.
Discover what makes Fivetran's Salesforce connector the simplest way to move your entire Salesforce org into the warehouse without all the operational complexity.
Five paths give Fivetran the flexibility to connect virtually any data source, from SaaS applications and flat files to application databases, proprietary APIs, and real-time event streams.
As Superhuman expanded its AI platform across Grammarly, Coda, Superhuman Mail, and Superhuman Go, more of the business began to rely on timely data from Salesforce, Outreach, Pardot, Stripe, Zendesk, Qualtrics, and other third-party systems. The challenge went far beyond moving data into Databricks. Go-to-market, finance, and customer teams needed faster, reliable access to trusted data without turning every new data request into weeks of custom engineering.
As AI accelerates the pace of change, demanding fresher data, diverse formats, and support across multiple engines, many teams discover their infrastructure was built for reporting, not real-time AI at scale. Open Data Infrastructure is redefining how organizations design for analytics, operations, and AI. By leveraging Fivetran as an interoperable data foundation, organizations can embrace open standards, separate storage from compute, and keep data portable across clouds and engines, preserving adaptability while scaling AI and operational workloads with Databricks.
Healthcare organizations operate some of the most complex data environments, spanning thousands of systems across clinical, financial, and operational domains. At Inova Health, this complexity created an opportunity to rethink how data could better support analytics and AI at scale.
Learn what Debezium is, how its CDC architecture and connectors support MySQL and SQL Server, and which of the three deployment modes fits your pipeline.
As software vendors place more controls around data access, enterprises must decide whether their future AI capabilities will be defined by their strategy or their vendors' policies.