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Enterprise Data Analysis and Visualization: An Interview Study
S Kandel1, A Paepcke, J M Hellerstein
1Stanford University, USA. skandel@cs.stanford.edu
IEEE Transactions on Visualization and Computer Graphics
|September 11, 2015
Summary
Data analysts face challenges in enterprise environments. Understanding the social and organizational context is key to improving data analysis tools and processes.
Area of Science:
- Information Science
- Human-Computer Interaction
- Organizational Studies
Background:
- Organizations utilize data analysts for critical functions like customer engagement modeling, operational streamlining, and fraud detection.
- Existing analysis and visualization tools lack research on their integration within the social and organizational context of companies.
Purpose of the Study:
- To investigate the ecosystem of enterprise data analysts.
- To understand how organizational features impact industrial data analysis processes.
- To identify challenges and barriers in adopting visual analytic tools.
Main Methods:
- Conducted semi-structured interviews with 35 data analysts.
- Included participants from 25 organizations across diverse sectors (healthcare, retail, marketing, finance).
Main Results:
- Characterized the industrial data analysis process.
- Documented the impact of organizational features on data analysis.
- Identified recurring pain points, challenges, and adoption barriers for visual analytic tools.
Conclusions:
- Organizational context significantly influences data analysis practices.
- There are opportunities for designing better visual analytic tools tailored to enterprise needs.
- Further research is needed to address identified challenges and improve tool adoption.
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