🚲 BikeStores Executive Sales Dashboard

📌 Project Overview

An end-to-end sales analytics project built on the BikeStores relational database. Raw transactional data is extracted using a multi-table SQL query, loaded into Excel, and visualized through an interactive Executive Sales Dashboard with slicers, KPI cards, and 7+ chart types.

This project demonstrates a complete data analyst workflow: SQL → Data Extraction → Excel Dashboard → Business Insights.

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🛠️ Tools & Technologies

• SQL Server — Multi-table joins, aggregations, data extraction
• Microsoft Excel — Pivot Tables, Pivot Charts, Slicers, Map Charts, KPI Cards

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📊 Dashboard Features

Section	Description
💰 KPI Cards	Total Revenue ($8.58M), Total Units Sold (7,078), Total Customers (4,722)
📅 Revenue per Year	Column chart comparing 2016–2018 annual revenue
📈 Monthly Revenue Trends	Multi-line chart showing monthly patterns across years
🗺️ Revenue per State	Bing-powered map chart (CA, NY, TX)
🥧 Revenue per Store	Pie chart with % breakdown across 3 stores
👤 Top 10 Customers	Horizontal bar chart ranked by revenue
📦 Top 10 Products	Horizontal bar chart ranked by revenue
🏷️ Revenue per Category	Bar chart by bike category
🧑‍💼 Sales by Rep	Sales representative contribution comparison

🎛️ Interactive Filters (Slicers)

• Year — Filter by 2016, 2017, 2018
• State — Filter by CA, NY, TX
• Store — Filter by Baldwin Bikes, Rowlett Bikes, Santa Cruz Bikes

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💡 Key Business Insights

• 📌 Baldwin Bikes dominates with 68% of total revenue ($5.82M), far ahead of Santa Cruz Bikes (21%) and Rowlett Bikes (11%)
• 📌 2017 was the peak year with $3.84M in revenue — a 42% increase over 2016
• 📌 Revenue declined in 2018 to $2.02M — worth investigating for seasonality or data cutoff
• 📌 Mountain Bikes is the top-selling category with $3.03M in revenue
• 📌 Top customer (Pamela Newman) contributed $37,802 — the top 3 customers are closely competitive
• 📌 Marcelene Boyer leads the sales team with $2.93M in personal sales contributions
• 📌 Trek Slash 8 27.5 - 2016 is the best-selling product at $615,998

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🗂️ Project Structure

BikeStores-Analysis/
├── README.md
├── sql/
│   └── Bike_Store_Analysis.sql       # Multi-table extraction query
├── dashboard/
│   └── BikeStores_Dashboard.xlsx     # Interactive Excel dashboard
└── screenshots/
    └── dashboard_preview.png         # Dashboard preview image

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⚙️ How to Run

Step 1 — Set up the Database

1. Download the BikeStores sample database from sqlservertutorial.net
2. Restore it in SQL Server Management Studio (SSMS)

Step 2 — Run the SQL Query

1. Open sql/Bike_Store_Analysis.sql in SSMS
2. Execute the query — it will return the flat dataset used by the dashboard

Step 3 — Refresh the Dashboard

1. Open dashboard/BikeStores_Dashboard.xlsx
2. If connected to your local SQL Server: go to Data → Refresh All
3. All pivot tables and charts will update automatically

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🗃️ Data Source

BikeStores Sample Database — a fictional bicycle retail dataset commonly used for SQL training, provided by sqlservertutorial.net.

The database includes 9 tables across two schemas:

• sales — orders, customers, order_items, stores, staffs
• production — products, categories, brands, stocks

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👤 Author

Aditya Kumar

• LinkedIn: linkedin.com/in/xaditya

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