Avalilação PREreview Estruturada de SiriusBI: A Comprehensive LLM-Powered Solution for Data Analytics in Business Intelligence

Does the introduction explain the objective of the research presented in the preprint?

Yes

The paper clearly states its goal: to design an end-to-end BI system that integrates LLMs for query understanding, semantic modeling, and automated reporting.

Are the methods well-suited for this research?

Somewhat appropriate

They propose a modular pipeline: LLM-based natural language query interpretation, schema alignment, and auto-report generation. Strong approach, but evaluation is more prototype-level.

Are the conclusions supported by the data?

Somewhat supported

Their demo cases show LLMs improve flexibility in BI workflows. Results support the claims but remain limited to lab environments.

Are the data presentations, including visualizations, well-suited to represent the data?

Somewhat appropriate and clear

Diagrams illustrate architecture well, but figures could be simplified.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Somewhat clearly

Authors discuss extending SiriusBI to enterprise settings and scaling with more diverse datasets. Next steps are suggested, but more detail on risks (e.g., hallucinations, cost) would help.

Is the preprint likely to advance academic knowledge?

Somewhat likely

Novel: few works connect end-to-end BI pipelines with LLMs. Incremental in terms of architecture, but meaningful.

Would it benefit from language editing?

Yes

Mostly readable, with some awkward phrasing.

Would you recommend this preprint to others?

Yes, but it needs to be improved

Is it ready for attention from an editor, publisher or broader audience?

Yes, after minor changes

Competing interests

The author declares that they have no competing interests.