data-analysis-report-agent

Hypothesis-driven data analysis is automated by iteratively exploring data and reflecting on findings to generate interactive HTML reports. This workflow applies structured frameworks to validate business conclusions and visualize results using ECharts.

Preventing LLM hallucinations during data analysis requires hard-coded validation via a harness layer. This ensures data source traceability and logical consistency, shifting from superficial data retelling to verifiable, attribution-driven business intelligence.

Identifying the root cause of a profit margin decline is achieved by applying an automated, iterative analytical plan to complex sales data. The agent explores structured data across product categories to synthesize traceable business conclusions.

Automated reporting with this agent fully supports interactive ECharts visualizations for business intelligence. It generates professional HTML reports that visualize structured data exploration and attribution analysis findings.

Validating business conclusions against raw data sources is a core capability of this data analysis agent. It applies hard-coded validation rules to ensure data traceability and logical consistency throughout the iterative refinement process.

Limitations of superficial data retelling include lack of attribution and inability to verify conclusions against raw data. Structured data exploration overcomes this by enforcing hard-coded validation and iterative hypothesis refinement.