Spotify Music Insights Dashboard Using Tableau

1.       Sri Thanvi, UG scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.

2.       Komal Kumari, UG scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.

3.       Anisha Koshika, UG scholar Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India.

4.       Mr.CH.Nagarjuna, Professor, Department of AI&DS, Methodist College of Engineering and Technology, Hyderabad, India,

ABSTRACT

Spotify is one of the world’s largest music streaming platforms, generating vast amounts of data on songs, artists, streams, and audio features. This project explores Spotify music data from 2023 using Tableau, a powerful data visualization tool, to uncover meaningful patterns in song popularity, artist performance, streaming trends, and audio feature correlations. The dateset includes 953 tracks with 24 attributes such as streams, dance-ability, energy, tempo, and musical key. Through interactive dashboards, bar charts, line charts, scatter plots, heat-map, and tree-maps, the analysis highlights key findings-such as Blinding Lights being most streamed song with 2.88B streams, Taylor Swift dominating with 14B+ total streams, and high-energy, high-dance ability songs correlating with higher streaming success. The project also identifies a clear upward trend in streaming popularity after 2015. These insights are valuable for music analysts, record labels, artists, playlist curators, and streaming platforms. By transforming complex data into intuitive visual stories, this Tableau-driven study enhances understanding of music consumption patterns and supports data driven decision making in the music industry.