Task: equi-join-detect (source dataset: Auto-BI)

Your are given a database with related tables used for business intelligence analysis. Your task is to identify all key/foreign-key join relationships between the tables for this database. Recall that a join is a relationship between two tables, that allows rows from one table to be combined with rows from another, based on a set of common join columns.
 
 
No explanation needed. Please return all join relationships in the following JSON format:
{
  "joins": [
    {
      "from_table": "table-1",
      "from_column": "column-1",
      "to_table": "table-2",
      "to_column": "column-3"
    }, 
	...
  ]
}

Tables:

Table: Customers
| Customer ID   | Customer Name    | Segment     |
|:--------------|:-----------------|:------------|
| CustID- 401   | Selorm Addo      | Consumer    |
| CustID- 525   | Peter Ankoma     | Consumer    |
| CustID- 214   | Priscilla Mintah | Consumer    |
| CustID- 030   | Cecilia Esi      | Home Office |
| CustID- 204   | Francis Mensah   | Consumer    |
| CustID- 494   | Emmanuel Kwashie | Consumer    |
| CustID- 096   | Abdul Rawuf      | Home Office |
| CustID- 496   | Bridget Okyere   | Consumer    |
| CustID- 290   | Michael Gyasi    | Consumer    |
| CustID- 334   | Elikem Kobla     | Consumer    |


Table: Location
| City       | Country   | Region     |
|:-----------|:----------|:-----------|
| Tamale     | Ghana     | Northern   |
| Axim       | Ghana     | Western    |
| Ahwiaa     | Ghana     | Ashanti    |
| Tarkwa     | Ghana     | Western    |
| Mampong    | Ghana     | Ashanti    |
| Wa         | Ghana     | Upper West |
| Yendi      | Ghana     | Northern   |
| Cape Coast | Ghana     | Central    |
| Effiduase  | Ghana     | Ashanti    |
| Bolgatanga | Ghana     | Upper East |


Table: Product
| Product ID      | Category      | Sub-Category         | Product Name                                                                     |
|:----------------|:--------------|:---------------------|:---------------------------------------------------------------------------------|
| ProdID-28000011 | Electronics   | Accessories_Supplies | Power Supply Module for HKC 401-2K201-D4211 HKL-480201/500201/550201 Accessories |
| ProdID-28000021 | Phone_Tablets | Mobile Phones        | Apple iPhone 8 Plus Gold 64GB 256GB 4G LTE Unlocked Smartphone SIM Free          |
| ProdID-28000031 | Home_Office   | Furniture            | Printed Chair Cover Soft Milk Silk                                               |
| ProdID-28000041 | Phone_Tablets | Mobile Phones        | Apple iphone 8 plus locked ee red - 256 gb                                       |
| ProdID-28000051 | Electronics   | Accessories_Supplies | Power Supply Board Driver Board for Samsung T220 T220G T220 IP-49135B+ Accessory |
| ProdID-28000061 | Electronics   | Accessories_Supplies | Projector Accessories 4h.1dn40.a00 Mains Power Supply for BenQ ms500/mx501/ms5   |
| ProdID-28000071 | Phone_Tablets | Mobile Phones        | Apple iPhone 7 Plus 32GB 128GB 4G-LTE Entsperrt Smartphone 12M Warranty          |
| ProdID-28000081 | Home_Office   | Furniture            | Office suppliers                                                                 |
| ProdID-28000091 | Phone_Tablets | Mobile Phones        | SAMSUNG GALAXY S10 (VERIZON) SM-G973U 128GB W CHARGERS SEE THRU EF-ZG973 COVER   |
| ProdID-28000101 | Home_Office   | Furniture            | Bean bag                                                                         |


Table: Transactions
|   Row ID | Order ID           | Order Date              | Delivery Date           | Delivery Mode   | Customer ID   | City   | Product ID      |   Unit cost |   Quantity |   Selling price |   Discount |
|---------:|:-------------------|:------------------------|:------------------------|:----------------|:--------------|:-------|:----------------|------------:|-----------:|----------------:|-----------:|
|        1 | OrdID-2018-0000011 | 2018-01-06 00:00:00.000 | 2018-01-13 00:00:00.000 | 5-7 Day         | CustID- 401   | Tamale | ProdID-28000011 |         150 |         11 |             212 |  0.0749047 |
|        3 | OrdID-2018-0000031 | 2018-01-06 00:00:00.000 | 2018-01-08 00:00:00.000 | 2-3 Day         | CustID- 214   | Tamale | ProdID-28000031 |         290 |          8 |             343 |  0.05      |
|       18 | OrdID-2018-0000181 | 2018-01-20 00:00:00.000 | 2018-01-25 00:00:00.000 | 5-7 Day         | CustID- 453   | Tamale | ProdID-28000181 |        1747 |          6 |            2499 |  0.0833879 |
|       27 | OrdID-2018-0000271 | 2018-01-26 00:00:00.000 | 2018-01-28 00:00:00.000 | 2-3 Day         | CustID- 401   | Tamale | ProdID-28000271 |         292 |          3 |             363 |  0.04      |
|       33 | OrdID-2018-0000331 | 2018-02-02 00:00:00.000 | 2018-02-04 00:00:00.000 | 2-3 Day         | CustID- 271   | Tamale | ProdID-28000331 |         530 |          6 |             622 |  0         |
|       39 | OrdID-2018-0000391 | 2018-02-11 00:00:00.000 | 2018-02-13 00:00:00.000 | Pick up         | CustID- 102   | Tamale | ProdID-28000391 |         576 |          9 |             789 |  0.0542556 |
|       43 | OrdID-2018-0000431 | 2018-03-04 00:00:00.000 | 2018-03-06 00:00:00.000 | 2-3 Day         | CustID- 214   | Tamale | ProdID-28000431 |         256 |         15 |             342 |  0.101902  |
|       44 | OrdID-2018-0000441 | 2018-03-11 00:00:00.000 | 2018-03-12 00:00:00.000 | Express 1 Day   | CustID- 214   | Tamale | ProdID-28000441 |         240 |          1 |             304 |  0.09      |
|       59 | OrdID-2018-0000591 | 2018-03-17 00:00:00.000 | 2018-03-22 00:00:00.000 | 5-7 Day         | CustID- 102   | Tamale | ProdID-28000581 |         469 |         17 |             564 |  0.08      |
|       61 | OrdID-2018-0000611 | 2018-03-18 00:00:00.000 | 2018-03-23 00:00:00.000 | 5-7 Day         | CustID- 401   | Tamale | ProdID-28000601 |         603 |          1 |             863 |  0.138322  |

 


tables: name: Customers
data: Customers.csv
name: Location
data: Location.csv
name: Product
data: Product.csv
name: Transactions
data: Transactions.csv
label: Transactions
Customer ID
Customers
Customer ID
Transactions
City
Location
City
Transactions
Product ID
Product
Product ID
output: {
    "joins": [
        {
            "from_table": "Transactions",
            "from_column": "Customer ID",
            "to_table": "Customers",
            "to_column": "Customer ID"
        },
        {
            "from_table": "Transactions",
            "from_column": "City",
            "to_table": "Location",
            "to_column": "City"
        },
        {
            "from_table": "Transactions",
            "from_column": "Product ID",
            "to_table": "Product",
            "to_column": "Product ID"
        }
    ]
}