Data-driven use cases are increasingly important, and data sharing is a common focus. Data enables decisions through knowledge, and it powers AI use cases. Data products for specific use cases are the foundation of many business models. Data is not everything, but without data, everything is nothing.

In reality, it is often difficult for teams to share and collaborate on data. It remains in silos and operational data stores where it is not readily available, and costly integrations are required to gain access. This is especially an obstacle when organizations want to make data available to external consumers to drive new digital business models and revenue streams.

APIs could help overcome this by opening up interoperability. Using a real-world scenario, we show how our lightweight architectural approach based on the data mesh concept and leveraging a data platform bridges the gap between data products and APIs. Costly custom integration and overhead can be avoided. Instead, automation and configuration enable rapid deployment of independent, full-featured APIs with the added benefit of API management capabilities like access control or monetization. We share our experiences so you can apply the ideas to your own use cases.