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I’ve just completed my submission for the May 2026 #DataDNA Challenge by Onyx Data, where the goal was to analyse a 4-year music streaming platform dataset and uncover: 📈 Growth trends in listening, revenue, and subscriptions 👥 User behaviour and retention patterns 💳 Subscription lifecycle dynamics 🎵 Content monetisation by artist, genre, and geography ⚠️ Behavioural anomalies and suspicious patterns Built in Power BI, my dashboard explored: • Executive performance snapshot • Behaviour & retention analysis • Content monetisation & subscription growth drivers Some standout insights: 🔸 Casual Users dominate the platform (62.5%) but churn risk remains visible 🔸 Mobile users are the most engaged, while Car users show the highest churn risk 🔸 Organic drives the most signups, reconciliation drives the most upgrades 🔸 Pop monetises best, while Metal carries the highest churn risk 🔸 Behavioural anomalies affect 46.5% of users and may impact revenue quality
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