Spotify Songs Analysis

This project leverages Power BI to: - Analyze Spotify song data to provide insights into trends, listener preferences, and genre popularity.

- Visualize metrics such as streaming counts and song characteristics to help music curators, marketing teams, and artists make data-driven decisions.

- Optimize playlist recommendations and target specific audience segments to enhance user engagement on the platform.

- Perform a predictive analysis for emerging artists or trends to allow Spotify to remain competitive in the digital music landscape.

The following steps were completed:

- Download the dataset from Kaggle using this link: https://drive.google.com/file/d/1009ZQdqIQV1-TNqNt1rXENK4zFWM_55u/view?usp=drive_link

- Import the dataset to PostgreSQL and clean it to prepare for analysis.

- Import the cleaned dataset to Power BI and analyze it to uncover insights.

- Explore patterns in audio features to understand trends and preferences in popular songs.

- Analyze how artist involvement and attributes relate to a song's success.

- Investigate how songs perform across different streaming services.

- Build an interactive dashboard to communicate insights from the analysis and provide recommendations on how to enhance user experience on the platform.

The following tools were used:

- PostgreSQL to clean and prepare the data.

- Power BI to analyze the data and build the dashboard.

The analysis of Spotify streaming data has provided a comprehensive understanding of listener preferences, engagement patterns, and streaming trends. Key takeaways:

- Create specialized playlists around emotional songs with lower valence and energy to cater to listeners seeking more contemplative or moody music.

- Release new tracks during high-traffic months such as January, March, May, and June when streaming surges, capitalizing on audience activity during holidays or summer.

- Promote songs with high danceability and energy during periods associated with high activity, such as parties or events, to drive streams.

- Artists, marketers, and industry professionals can leverage the findings from this analysis to make data-driven decisions to optimize streaming strategies, increase fan engagement, and maximize revenue potential.