Systems | Development | Analytics | API | Testing

GitHub Copilot: Using AI to build a custom connector with Fivetran's Connector SDK

This tutorial demonstrates how to build a Fivetran Connector SDK custom connector using VS Code and GitHub Copilot. The demo showcases the end-to-end process of creating, testing, and deploying a connector that ingests tobacco problem reports from the openFDA API.

Cursor: Using AI to build a custom connector with Fivetran's Connector SDK

This tutorial demonstrates how to build a Fivetran Connector SDK custom connector using AI assistance with Cursor, an AI code editor. The demo showcases the end-to-end process of creating, testing, and deploying a connector for the FDA Food Enforcement API.

How leading enterprises use Fivetran to break down SAP data barriers

As we explored in our previous post, SAP’s ecosystem makes it costly and complex to centralize data, especially when organizations need to blend SAP and non-SAP sources for unified analytics. Between restrictive licensing, limited compatibility, and constrained export options, SAP’s architecture often creates more roadblocks than results.

A Guide to Reliable Files to Salesforce Integration

Salesforce remains the backbone of sales, marketing, and customer experience for enterprises around the world. Yet, for all its power, it still needs fuel: data. Often, this data lives in files—CSV exports, legacy system dumps, partner spreadsheets—waiting to be transformed and loaded into Salesforce. This guide unpacks everything technical professionals need to know about File to Salesforce integrations, especially in the context of enterprise-grade data pipelines.

Build Observable Data Flywheels for Production with Iguazio's MLRun and NVIDIA NeMo Microservices

We are proud to announce a new integration between MLRun, the open-source AI orchestration framework, and NVIDIA NeMo microservices, by extending NVIDIA Data Flywheel Blueprint. This integration streamlines training, evaluation, fine-tuning and monitoring of AI models at scale, ensuring high-performance, low latency and lowering costs while significantly reducing the manual effort required through intelligent automation.