Building a Business Intelligence Pipeline for GitHub Issue Analytics: Talend ETL, a MySQL Star Schema and Power BI

GitHub issues carry operational data about software quality, but they arrive as paginated, semi-structured JSON that is hard to analyze directly. This paper describes an end-to-end business intelligence pipeline that extracts issues from the GitHub REST API with Talend Open Studio, transforms them, and loads them into a MySQL data warehouse modeled as a star schema (one bug fact table and four dimensions: developer, project, status and priority). Dashboards in Power BI or Tableau support questions on status distribution, monthly trends, bugs per project and priority mix. We document three concrete integration failures and their fixes: a phantom column in the JSON-extraction schema, ISO 8601 date parsing, and MySQL authentication and SSL errors. The ETL was validated on a proof-of-concept load of 59 issues; the dashboards were designed against the warehouse schema, and the large-volume charts shown in the project report are illustrative rather than results of that load. We therefore present the work as a validated pipeline design and a template, not as an empirical study of bug data. Preprint, not peer reviewed.