
Zhikun Zheng developed a collaborative Excel data analysis feature for the eosphoros-ai/DB-GPT repository, focusing on enabling multi-agent processing of Excel files and automatic SQL query generation. Using Python, async programming, and SQL, Zhikun designed a workflow where teams can analyze Excel data together and generate database queries without manual SQL writing. This approach streamlines cross-functional data analysis and accelerates insight discovery by automating repetitive tasks. The work established a scalable foundation for future analytics enhancements, with integration points and documentation supporting extensibility. While the contribution was focused on a single feature, it demonstrated depth in data processing and workflow design.
October 2025: Delivered a collaborative Excel data analysis feature with automatic SQL generation for DB-GPT, enabling multi-agent processing of Excel data and automatic SQL query generation from Excel inputs. The work lays the foundation for cross-functional data analysis, accelerating insight discovery and reducing manual SQL effort.
October 2025: Delivered a collaborative Excel data analysis feature with automatic SQL generation for DB-GPT, enabling multi-agent processing of Excel data and automatic SQL query generation from Excel inputs. The work lays the foundation for cross-functional data analysis, accelerating insight discovery and reducing manual SQL effort.

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