DataVista: A Simplified Data Visualization Tool

DataVista is a simplified data visualization tool developed to address the challenges oftransforming raw, diverse datasets into actionable insights with minimal technical intervention.The project leverages a comprehensive design thinking approach, beginning with an empathyphase that employed surveys, interviews, and observational techniques to uncover the needs andpain points of its primary stakeholders—including students, data scientists, and data analysts.Insights gathered during this phase helped define the core challenges, such as data cleaning, multi-format compatibility, and the complexity of existing visualization tools. In the subsequent defineand ideation phases, the team framed the problem through targeted "How Might We" questionsand explored a wide range of innovative solutions using techniques like brainstorming, mindmapping, SCAMPER, and storyboarding. These sessions led to the conceptualization of featuressuch as one-click data upload, automated preprocessing, AI-powered visualizationrecommendations, customizable dashboards, and real-time data integration. The prototypingphase then transformed these ideas into tangible, testable components, ensuring that the finalproduct would be both user-friendly and robust.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-03-26
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.39783
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
1.28
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article

DataVista: A Simplified Data Visualization Tool

Regina Célia Coelho, Harsh Singh, S S Veerasagar, Nithyashree GD
1 citations
International Journal For Multidisciplinary Research
Data Visualization and Analytics
1.28
article

DataVista: A Simplified Data Visualization Tool

Regina Célia Coelho, Harsh Singh, S S Veerasagar, Nithyashree GD
article en
1 citations

Abstract

DataVista is a simplified data visualization tool developed to address the challenges oftransforming raw, diverse datasets into actionable insights with minimal technical intervention.The project leverages a comprehensive design thinking approach, beginning with an empathyphase that employed surveys, interviews, and observational techniques to uncover the needs andpain points of its primary stakeholders—including students, data scientists, and data analysts.Insights gathered during this phase helped define the core challenges, such as data cleaning, multi-format compatibility, and the complexity of existing visualization tools. In the subsequent defineand ideation phases, the team framed the problem through targeted "How Might We" questionsand explored a wide range of innovative solutions using techniques like brainstorming, mindmapping, SCAMPER, and storyboarding. These sessions led to the conceptualization of featuressuch as one-click data upload, automated preprocessing, AI-powered visualizationrecommendations, customizable dashboards, and real-time data integration. The prototypingphase then transformed these ideas into tangible, testable components, ensuring that the finalproduct would be both user-friendly and robust.

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 22%
Data Visualization and Analytics
1.28
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DataVista: A Simplified Data Visualization Tool — Regina Célia Coelho, Harsh Singh, et al. · International Journal For Multidisciplinary Research (2025) | TGRS Research Map | TGRS