5 ways Fivetran accelerates mergers and acquisitions
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.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Why you need to share data across tools
For humans and agents alike to use data effectively for future workloads, they need unified context, reduced friction, and flexibility.
5 reasons the Fivetran Salesforce connector just works
Discover what makes Fivetran's Salesforce connector the simplest way to move your entire Salesforce org into the warehouse without all the operational complexity.
Introducing Fivetran for Db2 for z/OS and Db2 for LUW
Fivetran’s Db2 portfolio is now complete, bringing modern analytics to all Db2 users.
No walled gardens: Amazon reversed its Seller Partner API fees
Amazon’s recent pivot on the Selling Partner API is an encouraging reminder that developer pushback can breach walled gardens.
AI requires unstructured data to unlock its full potential
Fivetran helps you turn unstructured data into rich context in several ways.
How to connect Fivetran to any data source
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.
Beyond centralization: Why APAC retail and CPG teams need activation
Centralizing data builds the foundation, but activating trusted data across operational systems will drive the next wave of growth in APAC.
8 Data Integration Platforms for Lending and Credit Fintechs (2026)
Lending and credit fintechs sit at the intersection of two hard problems: moving sensitive financial data fast enough to make timely credit decisions, and keeping that data secure enough to satisfy regulators, auditors, and enterprise security teams. The platforms that work for this use case share three traits. They replicate data with latency low enough to feed risk scoring models.
Building an AI-ready data foundation at Superhuman with Databricks and Fivetran
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.