Music Industry Analytics Dashboard

Role: Business Intelligence & Data Analyst | Timeline: July 2025 - Aug 2025
Tech Stack: Python, SQLite, Power BI, DAX

Overview

A comprehensive analytics system designed to transform fragmented Billboard chart data into actionable strategic intelligence. By consolidating streams, airplay, and sales into a unified view, this dashboard empowers music executives to make evidence-based promotional decisions.

The Challenge

Music industry decision-making is hindered by data fragmentation.

• Siloed Data: Streaming, airplay, and sales data exist in separate reporting streams, making cross-channel analysis difficult.
• Lack of Context: Traditional rankings show who is #1 but not why (e.g., is it radio-driven or viral streaming?).
• Manual Effort: Analysts spend hours manually correlating weekly charts in spreadsheets.

The Solution

I built a full-stack analytics pipeline that automates data ingestion and delivers interactive insights.

System Architecture

1. Data Engineering (Python/SQLite):

   • Developed automated ETL pipelines to ingest weekly chart data.
   • Implemented intelligent parsing algorithms to handle complex artist collaboration strings (e.g., "feat.", "x").
   • Designed a normalized database schema to track artist-song relationships over time.

2. Visualization (Power BI/DAX):

   • Created 50+ custom DAX measures for dynamic time-series analysis.
   • Built interactive views comparing Streaming vs. Airplay performance.

Impact & Results

• Strategic Clarity: Enabled executives to identify platform-specific performance gaps (e.g., high streaming but low radio).
• Operational Efficiency: Eliminated manual weekly data entry, saving hours of analyst time per week.
• Unified Truth: Created a single source of truth for cross-platform performance metrics.

Live Dashboard

Interact with the real Power BI report below. (Best viewed on Desktop).