🎧 Chinook Music Analytics Dashboard (Power BI + SQL)

🎵 Spotify-Inspired Music Store Insights Dashboard

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📘 Overview

The Chinook Music Analytics Dashboard is an end-to-end data visualization project built using Power BI and SQL Server.
It transforms the classic Chinook Database - a digital music store dataset - into an interactive and visually appealing analytics solution.

This project demonstrates advanced Power BI concepts including:

• DAX measures

• Drillthrough navigation

• Dynamic tooltips and slicers

• What-If parameter simulations

• Theming (Spotify-inspired UI)

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🧱 Data Source

Database: Chinook (Microsoft SQL Server)
Connection: Localhost (via SSMS)
Tables Used:
Customer, Invoice, InvoiceLine, Track, Album, Artist, Genre, Employee, MediaType

SQL Queries:
📄 All transformation and analysis queries used in Power BI are stored in SQLQueries.sql

Queries include:

• Revenue by Artist, Album, Genre
• Customer purchase summaries
• Invoice-level aggregations
• Date-based breakdowns for YoY and MoM

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📊 Power BI Dashboard Pages

1️⃣ Sales Overview

KPIs:

• Total Revenue, Total Units Sold, Avg Order Value

• YoY% and MoM% Growth
  Visuals:

• Sales & Units Sold (Map)

• KPI Cards

• Slicers → Year, Genre, Country

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2️⃣ Genre & Artist Insights

KPIs:

• Track Count, Total Artists, Total Albums
  Visuals:

• Top 10 Genres and Artists by Revenue

• List Slicers for Genre & Artist
  Features:

• Drilldown Hierarchy → Genre → Artist → Track

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  3️⃣ Tracks and Album Insights Page

Usage:
Right-click on an Artist in Genre & Artist Insights → Drillthrough → Artist Drillthrough
Visuals:

• Detailed Track List
• Track Revenue by Album
• Revenue by Country
• Total Units Sold
• Dynamic Title → Selected Artist

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4️⃣ Customer Insights

KPIs:

• No. of Repeat Customers

• Repeat Rate (%)

• Avg Revenue per Customer

• Median Historical CLV

• CLV Uplift %

• Projected CLV
  Visuals:

• Customer Tier (Basic Invoice counts)

• Customer Count by Country
  Features:

• CLV Projection

• Dynamic Segmentation

• Repeat Rate Analysis

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5️⃣ Revenue Simulation

What-If Scenarios:

• Revenue Growth %
• Discount %
  Visuals:
• Decomposition Tree (Genre → Artist → Country)

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🧮 Key Technical Highlights

Area	Feature	Description
Data Modeling	Star Schema	Fact (Invoices, InvoiceLines) linked to Dimension (Customer, Artist, Genre) tables
DAX	Advanced Measures	YoY%, MoM%, CLV, Repeat Rate, Dynamic KPIs
Visualization	Spotify-Inspired Theme	Dark background, Spotify green accents
User Experience	Drillthrough, Tooltips, Sync Slicers	Enhances navigation and interactivity
Scenario Analysis	What-If Parameters	Interactive sliders for revenue simulation

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📈 Insights Summary

• 📊 Sales Performance: Identify top-selling regions and analyze monthly revenue trends.
• 🎤 Artists: Discover which artists generate the most revenue and engagement.
• 🎶 Genres: Compare popularity, revenue, and profitability across different music genres.
• 👥 Customers: Understand retention, repeat rate, and Customer Lifetime Value (CLV) uplift.
• 💡 Simulation: Model revenue impact under varying growth and discount scenarios.

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🧰 Tools & Technologies

• Power BI Desktop (May 2025 Update)
• Microsoft SQL Server (SSMS)
• DAX
• Power Query (ETL)
• GitHub (Version Control & Documentation)

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👨‍💻 Author

Priyasi Shah

📧 mailto:shahpriyasi1111@gmail.com

💼 https://www.linkedin.com/in/priyasi-shah/

🌐 https://github.com/PriyasiShah1211