# A Conceptual Model for Data Storytelling Highlights in Business Intelligence Environments

arXiv: https://arxiv.org/abs/2403.00981 · HTML: https://mlsanity.com/paper/2403.00981/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Mar 2024.

## Built on by (most cited first, 1 of 1)

- [Unveiling Interesting Insights: Monte Carlo Tree Search for Knowledge Discovery](https://mlsanity.com/paper/2510.00876/) (2025)

## Abstract (arXiv)

We introduce a conceptual model for highlights to support data analysis and storytelling in the domain of Business Intelligence, via the automated extraction, representation, and exploitation of highlights revealing key facts that are hidden in the data with which a data analyst works. The model builds on the concepts of Holistic and Elementary Highlights, along with their context, constituents and interrelationships, whose synergy can identify internal properties, patterns and key facts in a dataset being analyzed.