Personalization and Individual Differences in Business Data Analytics

Abstract

Today’s data-driven business environment necessitates the adoption of business intelligence and analytics (BI &A) platforms for companies that want to remain competitive or even survive in the global market. On the other hand, as the volume and variety of data grow, the ability to quickly analyze data and reach actionable decisions becomes more complex. In response, BI &A vendors have developed features, to assist users with data exploration, analysis, and delivery of on-demand timely business insights using interactive data visualizations. These tools also enable non-expert analysts, such as directors, to quickly translate data into actionable items. However, the large variety of tools and data visualizations may become overwhelming and diminish the end users’ ability to quickly reach a decision. Furthermore, BI &A vendors adopt the on-size-fits-all approach, delivering the same output to all users for identical requests, neglecting to incorporate their unique characteristics and personalize their interaction. This chapter presents the user adaptation and personalization techniques employed by leading BI &A enterprise solutions, and discusses the effect of individual differences in understanding and processing data visualizations. Our goal is to explore opportunities and challenges of incorporating individual differences in the visual analytics process, and highlight the necessity of a human-centered model in BI &A platforms.