Business Visualization Overview

Principles

Definition

Business visualization is a distinct area within business analytics and data science focused on the systematic transformation of complex business data into insightful visual formats. It investigates the principles and methods by which graphical representations effectively communicate patterns, trends, and relationships, thereby supporting strategic analysis, facilitating understanding, and enabling data-driven decision-making within organizational contexts.

Ontological type

Core Methods

Design Principles

Business Applications

Key developments

Key Figures

Interactive Multiview Exploration era

Jarke J. van Wijk [1] is a leading figure associated with the University of Amsterdam [3] and Eindhoven University of Technology [4] during the Interactive Multiview Exploration era. His key contributions include advancing Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges [7], evaluating Cluster Identification Performance for Different PCP Variants [8], and Visual Inspection of Multivariate Graphs [9], which collectively advanced large-graph visualization, rigorous evaluation, and multivariate representations central to coordinated views in this era. Jean‐Daniel Fekete [2] is associated with Université Paris-Sud [5] and Université Paris Cité [6], contributing to Visualization Summit 2007: Ten Research Goals for 2010 [10] and Visual Analysis of Large Graphs [7], shaping the era's design goals for interactive dashboards and scalable visualization. Jean‐Daniel Fekete [2] helped orient this era by articulating ten research goals for 2010 [10] and by contributing to Visual Analysis of Large Graphs [7], anchoring coordinated views, focus-and-context, and dashboard-oriented interaction that defined this era.

Enterprise Visual Analytics era

Jeffrey Heer [1], associated with Stanford University [3] and the University of Washington [4] in this era, contributed to two influential works on enterprise data analysis and visualization: Enterprise Data Analysis and Visualization: An Interview Study [7] (2012) and Lyra: An Interactive Visualization Design Environment [8] (2014). The Interview Study [7] and Lyra [8] provided early design guidance for enterprise visualization, highlighting governance, visualization literacy, and interactive design needs essential for building scalable, model-driven analytic pipelines across organizational systems. Joseph M. Hellerstein [2], affiliated with University of California, Berkeley [5] and Berkeley College [6], contributed to the Enterprise Data Analysis and Visualization: An Interview Study [7] in this era. His key contribution, as reflected in the Interview Study [7], was the empirical documentation of data integration, analytics workflows, and governance needs that informed the design of enterprise-scale visual analytics pipelines for automated, repeatable decision support.