Data Products are not standalone entities. They create a dynamic web of connections that boost business intelligence and fuel innovation across the entire enterprise.
To manage data effectively, it is necessary to iterate continuously from its discovery to its eventual deprecation.
Before writing any pipeline code, it is important to first identify consumer needs, establish SLAs, and create a semantic schema model.
Create logic for data ingestion, implement transformations, and conduct thorough data quality tests through CI/CD pipelines.
Implement the product in the data catalog, enable access for consumers through output ports, and initiate SLA monitoring.
Update the product according to user feedback, or discontinue it if it no longer adds value to the business.
Output ports from one domain are transformed into input ports for another, enabling a federated approach that eliminates bottlenecks and enables the secure creation of complex, composite data products on top of foundational ones.
Transition from centralized engineering teams facing bottlenecks to a decentralized, domain-focused data ecosystem.