Worked on the Causal-Copilot repository to establish a foundational data ingestion and analytics workflow supporting real-world datasets. Developed features in Python using Pandas and JSON handling to enable loading of external data from file paths, with robust error handling for unsupported formats such as non-CSV or non-JSON files. Implemented a user query processing system that parses and filters queries, identifies relevant algorithms, and stores processed results for downstream analysis. This work created an end-to-end pipeline for data loading and query-driven analytics, providing a scalable base for reproducible experiments and supporting future data-driven decision-making within the project’s architecture.