Building a Metadata-Driven Runtime API Platform for Analytics Systems
1. Business Problem
When I joined this project as a consultant, I almost said no. The client had already gone through several attempts before I joined the project, and the scope looked too complex to be practical. But I sat down, mapped out the risks, aligned expectations, and took it. That decision turned into one of the most technically interesting projects of my consulting career.
The company was building analytics solutions for different customers. Data flowed through ETL pipelines, machine learning models, and custom analytics processes. The final result was a massive amount of processed data that had to be exposed via web applications.
Since every customer had different requirements, database schemas, and ways to display information, we couldn't just build one backend and reuse it. The frontend was a Single Page Application that required a huge number of APIs. As a result, development teams repeatedly had to implement data models, APIs, filtering, sorting, pagination, and CRUD operations from scratch. Every new project meant supporting new schema changes and analytics requirements, so development and maintenance costs just kept growing.
