A Conceptual Model for Data Storytelling Highlights in Business Intelligence Environments
Panos Vassiliadis, Patrick Marcel, Faten El Outa, Veronika Peralta,, Dimos Gkitsakis

TL;DR
This paper presents a conceptual model for automated data highlights in Business Intelligence, aiding analysts in uncovering key insights through structured representation of data patterns and facts.
Contribution
It introduces a novel conceptual framework for highlights, integrating holistic and elementary highlights to enhance data storytelling in BI environments.
Findings
Defines a new model for data highlights in BI
Shows how highlights reveal hidden key facts
Supports improved data analysis and storytelling
Abstract
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.
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Taxonomy
TopicsData Visualization and Analytics · Video Analysis and Summarization · Big Data and Business Intelligence
