The early stages of product development are crucial to scalability in later stages. Product teams plan and build for scalability as best they can. To ensure marketing fit, teams will compromise scalability to create an agile and adaptable product in a market. With this understanding, let’s talk about why a GraphQL Data Layer can be injected at any stage in development and improve scalability, development flow, and communication between data sources and applications without hindering the adaptability of a product. Type system via the GraphQL specification. The types defined in the GraphQL schema create a compatibility layer between the frontend and backend that must be followed for successful compilation and deployment. Introspection of REST API JSON, database and GraphQL schemas to automate a continuous integration of data changes from backend data sources. The Data Layer modifies the GraphQL schema to match new data changes for continuous frontend deployment cycles. A Graph based model consolidates all data into an abstract syntax tree for easier and performant data linking. Transform data within the Data Layer to improve ETL flows and reduce business logic in frontend and backend applications. All the solutions above can be integrated at any stage of development. As a product scales and grows, a GraphQL Data Layer reduces manual back-and-forth communication between data sources and user facing applications.