The Integration of Data Science and Data Visualization: Achieving Digestible Insights Through Contemporary Platforms
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| Titel: | The Integration of Data Science and Data Visualization: Achieving Digestible Insights Through Contemporary Platforms |
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| Autoren: | Kiljan, Meredith |
| Verlagsinformationen: | Zenodo, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | matplotlib, ethical data visualization, plotly, big data, power bi, data visualization, data science, tableau, usability in visualization, augmented reality in visualization, python visualization libraries, adaptive visualizations, interactive dashboards, complex data sets |
| Beschreibung: | The integration of data science and data visualization has emerged as a transformative approach to processing, interpreting, and communicating complex datasets. This paper investigates the convergence of these fields to determine the most effective methods for creating user-friendly, digestible visualizations using platforms such as Tableau, Power BI, and Python libraries like Matplotlib and Plotly. Using a context analysis methodology, the study synthesizes insights from 25 peer-reviewed articles to evaluate usability, functionality, and effectiveness across various tools. Findings reveal that merging computational power with user-centric design principles significantly enhances the clarity and accessibility of data. Key themes include the importance of interactivity, scalability, and ethical considerations in visualization design. Future directions highlight the potential of adaptive visualization systems, augmented reality (AR), and virtual reality (VR) to revolutionize data analysis. This study contributes to the growing body of knowledge on leveraging data science and visualization for actionable, data-driven insights. keywords: data visualization, data science, Tableau, Power BI, Python visualization libraries, interactive dashboards, big data, usability in visualization, adaptive visualizations, augmented reality in visualization, ethical data visualization |
| Publikationsart: | Journal |
| Sprache: | English |
| DOI: | 10.5281/zenodo.14721872 |
| DOI: | 10.5281/zenodo.14721873 |
| Rights: | CC BY |
| Dokumentencode: | edsair.doi.dedup.....1c22f21b741a1e9a3f95a51a29ad55d7 |
| Datenbank: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | The integration of data science and data visualization has emerged as a transformative approach to processing, interpreting, and communicating complex datasets. This paper investigates the convergence of these fields to determine the most effective methods for creating user-friendly, digestible visualizations using platforms such as Tableau, Power BI, and Python libraries like Matplotlib and Plotly. Using a context analysis methodology, the study synthesizes insights from 25 peer-reviewed articles to evaluate usability, functionality, and effectiveness across various tools. Findings reveal that merging computational power with user-centric design principles significantly enhances the clarity and accessibility of data. Key themes include the importance of interactivity, scalability, and ethical considerations in visualization design. Future directions highlight the potential of adaptive visualization systems, augmented reality (AR), and virtual reality (VR) to revolutionize data analysis. This study contributes to the growing body of knowledge on leveraging data science and visualization for actionable, data-driven insights. keywords: data visualization, data science, Tableau, Power BI, Python visualization libraries, interactive dashboards, big data, usability in visualization, adaptive visualizations, augmented reality in visualization, ethical data visualization |
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| DOI: | 10.5281/zenodo.14721872 |