Power BI Streaming Intelligence Dashboard

Executive summary

A Power BI dashboard built from a cleaned synthetic streaming dataset of 7,957 rows. It covers 22 countries, five regions, 48 artists, nine genres, and 36 months from January 2022 to December 2024.

Business context

The dashboard is designed to answer a straightforward investment question: where should a global streaming business put attention when markets differ in revenue, conversion, listening behaviour, artist demand, and growth rate?

Data and preparation

The dataset was generated to reflect regional ARPU differences, genre preference, seasonal listening, playlist engagement, and premium conversion. Python prepared the data and spotify_clean.csv became the Power BI source, keeping the reporting layer separate from the preparation step.

Method

The dashboard compares revenue by market and quarter, artist and genre contribution, premium conversion, skips, playlist engagement, and regional growth. The visuals are paired with a presentation so the findings are not left as a collection of charts.

Results, limits, and next step

Q4 is the strongest revenue period in every year. Europe leads ARPU with premium conversion between 68 and 72 percent, while Africa has the fastest growth path through Nigeria, South Africa, and Kenya. Genre performance is regional rather than global. The dataset is synthetic, so the next step would be validating the same measures against production listening and billing data.