# A tibble: 527,913 × 6
Day Supplier Distribution_Center Product_Category Shipped_Volume
<dbl> <chr> <chr> <chr> <dbl>
1 0 S27 A Bakery 5
2 0 S28 A Bakery 4
3 0 S29 A Bakery 4
4 0 S30 A Bakery 2
5 0 S27 C Bakery 4
6 0 S28 C Bakery 9
7 0 S29 C Bakery 7
8 0 S30 C Bakery 4
9 0 S27 E Bakery 5
10 0 S28 E Bakery 4
# ℹ 527,903 more rows
# ℹ 1 more variable: Production_Volume <dbl>This has the raw data used for this project. This data talks about each layer in the Multi-Echelon Supply Chain.
Note
Samples of the Raw Data is provided as the data is large. However, I provided an option to download.
1 Supplier Data
2 Distribution Center Data
# A tibble: 95,160 × 6
Day Distribution_Center Restaurant Product_Category Shipped_Volume
<dbl> <chr> <dbl> <chr> <dbl>
1 0 A 1 Bakery 14
2 0 C 1 Bakery 23
3 0 E 1 Bakery 13
4 0 A 1 Beverages 60
5 0 C 1 Beverages 47
6 0 E 1 Beverages 71
7 0 C 1 Dairy 49
8 0 E 1 Dairy 38
9 0 A 1 Meat 20
10 0 C 1 Meat 13
# ℹ 95,150 more rows
# ℹ 1 more variable: Received_Volume <dbl>3 Restaurant Received Data
# A tibble: 36,600 × 4
Day Restaurant Product_Category Received_Order_Volume
<dbl> <dbl> <chr> <dbl>
1 1 1 Bakery 50
2 1 1 Beverages 178
3 1 1 Dairy 87
4 1 1 Meat 52
5 1 1 Vegetables 167
6 1 2 Bakery 41
7 1 2 Beverages 109
8 1 2 Dairy 63
9 1 2 Meat 43
10 1 2 Vegetables 125
# ℹ 36,590 more rows4 Restaurant Sales Data
# A tibble: 51,240 × 4
Day Restaurant Menu_Item Quantity_Sold
<dbl> <dbl> <chr> <dbl>
1 1 1 Burger 65
2 1 1 Coffee 78
3 1 1 Fries 58
4 1 1 Milkshake 61
5 1 1 Pizza 64
6 1 1 Salad 67
7 1 1 Soft Drink 72
8 1 2 Burger 54
9 1 2 Coffee 35
10 1 2 Fries 41
# ℹ 51,230 more rows