├── Data-mining report.docx
└── data-mining script.sql


/Data-mining report.docx:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/Rahat-karim/Data-mining-project/de60fc741e6a3bcca42d221762eada74b3c24816/Data-mining report.docx


--------------------------------------------------------------------------------
/data-mining script.sql:
--------------------------------------------------------------------------------
 1 | -- create schema retailshop;
 2 | -- use retailshop;
 3 | -- select * from online_retail;
 4 | 
 5 | -- Define Metadata:
 6 | DESCRIBE online_retail;
 7 | 
 8 | -- Distribution of Order Values Across All Customers:
 9 | SELECT CustomerID, SUM(UnitPrice * Quantity) AS OrderValue
10 | FROM online_retail
11 | GROUP BY CustomerID;
12 | 
13 | -- Number of Unique Products Each Customer Purchased:
14 | SELECT CustomerID, COUNT(DISTINCT StockCode) AS UniqueProductsPurchased
15 | FROM online_retail
16 | GROUP BY CustomerID;
17 | 
18 | -- Customers Who Have Made Only One Purchase:
19 | SELECT CustomerID
20 | FROM online_retail
21 | GROUP BY CustomerID
22 | HAVING COUNT(DISTINCT InvoiceNo) = 1;
23 | 
24 | -- Most Commonly Purchased Products Together:
25 | SELECT a.StockCode AS Product1, b.StockCode AS Product2, COUNT(*) AS TimesPurchasedTogether
26 | FROM online_retail a
27 | JOIN online_retail b ON a.InvoiceNo = b.InvoiceNo AND a.StockCode < b.StockCode
28 | GROUP BY Product1, Product2
29 | ORDER BY TimesPurchasedTogether DESC
30 | LIMIT 10;
31 | 
32 | -- Advanced Queries:
33 | -- Customer Segmentation by Purchase Frequency:
34 | SELECT CustomerID, 
35 |        COUNT(DISTINCT InvoiceNo) AS TotalPurchases,
36 |        CASE 
37 |            WHEN COUNT(DISTINCT InvoiceNo) >= 20 THEN 'High Frequency'
38 |            WHEN COUNT(DISTINCT InvoiceNo) BETWEEN 10 AND 19 THEN 'Medium Frequency'
39 |            ELSE 'Low Frequency'
40 |        END AS PurchaseFrequencySegment
41 | FROM online_retail
42 | GROUP BY CustomerID;
43 | 
44 | -- Average Order Value by Country:
45 | SELECT Country, AVG(UnitPrice * Quantity) AS AvgOrderValue
46 | FROM online_retail
47 | GROUP BY Country;
48 | 
49 | -- Customer Churn Analysis
50 | SELECT CustomerID
51 | FROM online_retail
52 | WHERE InvoiceDate < CURDATE() - INTERVAL 6 MONTH
53 | GROUP BY CustomerID;
54 | 
55 | -- Product Affinity Analysis:
56 | SELECT a.StockCode AS Product1, b.StockCode AS Product2, COUNT(*) AS PurchaseTogether
57 | FROM online_retail a
58 | JOIN online_retail b ON a.InvoiceNo = b.InvoiceNo AND a.StockCode < b.StockCode
59 | GROUP BY Product1, Product2
60 | ORDER BY PurchaseTogether DESC;
61 | 
62 | -- Time-Based Analysis
63 | SELECT YEAR(InvoiceDate) AS Year, MONTH(InvoiceDate) AS Month, SUM(UnitPrice * Quantity) AS TotalSales
64 | FROM online_retail
65 | GROUP BY Year, Month
66 | ORDER BY Year, Month;


--------------------------------------------------------------------------------