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: Articles
|   ArticleID |   ManufacturerID | Category    | Products                        | Color   | Model   | Trademark   | Origin   |   CostPrice |   Coverage, % |   SellingPrice |
|------------:|-----------------:|:------------|:--------------------------------|:--------|:--------|:------------|:---------|------------:|--------------:|---------------:|
|     3761351 |                1 | Accessoarer | 2-pack Cykelvantar              | Grå     | Mixed   | ProSport    | Kina     |       10.98 |          0.78 |           49.9 |
|     3761352 |                2 | Accessoarer | 2-pack Cykelvantar              | Svart   | Mixed   | FreeSport   | Kina     |       10.98 |          0.78 |           49.9 |
|     4675491 |                1 | Accessoarer | 2-pack smartphone-vantar        | Svart   | Mixed   | ProSport    | Kina     |       17.58 |          0.78 |           79.9 |
|     4675492 |                2 | Accessoarer | 2-pack smartphone-vantar        | Grå     | Mixed   | FreeSport   | Kina     |       17.58 |          0.78 |           79.9 |
|     2450991 |                1 | Accessoarer | Breda hängslen                  | Svart   | Mixed   | ProSport    | Kina     |       21.78 |          0.78 |           99   |
|     2029271 |                1 | Accessoarer | Cykelvantar med handledsvärmare | Svart   | Mixed   | ProSport    | Kina     |       10.98 |          0.78 |           49.9 |
|     2029272 |                2 | Accessoarer | Cykelvantar med handledsvärmare | Grå     | Mixed   | FreeSport   | Kina     |       10.98 |          0.78 |           49.9 |
|     2029273 |                3 | Accessoarer | Cykelvantar med handledsvärmare | Brun    | Mixed   | ProSport    | Kina     |       10.98 |          0.78 |           49.9 |
|     4610941 |                1 | Accessoarer | Fleecehandskar                  | Svart   | Mixed   | ProSport    | Kina     |       32.78 |          0.78 |          149   |
|     5978311 |                1 | Accessoarer | Fleecemössa                     | Svart   | Mixed   | ProSport    | Kina     |       17.58 |          0.78 |           79.9 |


Table: CustomerClub
|   CustomerID | Firstname   | Surname   |   Age | AgeRange   | Gender   | City      | County         |   AnnualIncome | IncomeGroup       |
|-------------:|:------------|:----------|------:|:-----------|:---------|:----------|:---------------|---------------:|:------------------|
|        26530 | Margareta   | Eriksson  |    31 | 30-39 år   | Kvinna   | Stockholm | Stockholms län |         542138 | 500 tkr eller mer |
|        26533 | Maria       | Olsson    |    38 | 30-39 år   | Kvinna   | Stockholm | Stockholms län |         261469 | 250-300 tkr       |
|        26548 | Linnéa      | Olsson    |    27 | 20-29 år   | Kvinna   | Stockholm | Stockholms län |         328032 | 300-400 tkr       |
|        26558 | Karin       | Johansson |    52 | 50-59 år   | Kvinna   | Stockholm | Stockholms län |         576864 | 500 tkr eller mer |
|        26564 | Emma        | Olsson    |    45 | 40-49 år   | Kvinna   | Stockholm | Stockholms län |         549864 | 500 tkr eller mer |
|        26568 | Eva         | Persson   |    29 | 20-29 år   | Kvinna   | Stockholm | Stockholms län |         532309 | 500 tkr eller mer |
|        26574 | Ingrid      | Larsson   |    33 | 30-39 år   | Kvinna   | Stockholm | Stockholms län |         224210 | 200-250 tkr       |
|        26576 | Elisabeth   | Larsson   |    18 | < 20 år    | Kvinna   | Stockholm | Stockholms län |         498004 | 400-500 tkr       |
|        26584 | Margareta   | Persson   |    41 | 40-49 år   | Kvinna   | Stockholm | Stockholms län |         596164 | 500 tkr eller mer |
|        26589 | Maria       | Persson   |    29 | 20-29 år   | Kvinna   | Stockholm | Stockholms län |         320955 | 300-400 tkr       |


Table: Manufacturer
|   ManufacturerID | Manufacturer   | Headquarter    | Certified      |
|-----------------:|:---------------|:---------------|:---------------|
|                1 | Abibas         | USA            | Ej certifierad |
|                2 | Akis           | Storbritannien | Certifierad    |
|                3 | Arrivo         | Frankrike      | Certifierad    |
|                4 | Girman         | Danmark        | Ej certifierad |
|                5 | Palor          | Italien        | Certifierad    |
|                6 | Pholops        | Japan          | Certifierad    |
|                7 | Roobeck        | Kina           | Ej certifierad |
|                8 | Schnell        | Tyskland       | Certifierad    |


Table: Stores
|   StoreID | StoreType        | StoreLocation   |
|----------:|:-----------------|:----------------|
|      1013 | Galleributik     | Umeå            |
|      1025 | Mellanstadsbutik | Umeå            |
|      1113 | Galleributik     | Gävle           |
|      1125 | Mellanstadsbutik | Gävle           |
|      1134 | Storstadsbutik   | Gävle           |
|      1213 | Galleributik     | Uppsala         |
|      1214 | Storstadsbutik   | Uppsala         |
|      1225 | Mellanstadsbutik | Uppsala         |
|      1313 | Galleributik     | Västerås        |
|      1325 | Mellanstadsbutik | Västerås        |


Table: Transactions
|   VerificationID | Date                    |   StoreID |   CustomerID |   ArticleID | Size   |   Quantity | Discount, %   |   DiscountAmount |   Amount | Payment   |
|-----------------:|:------------------------|----------:|-------------:|------------:|:-------|-----------:|:--------------|-----------------:|---------:|:----------|
|          6321972 | 2019-12-31 00:00:00.000 |      1782 |        26785 |     5868365 | M      |          1 |               |                0 |       99 | Kort      |
|          6321563 | 2019-12-06 00:00:00.000 |      1782 |        26933 |     5868365 | M      |          1 |               |                0 |       99 | Faktura   |
|          6321350 | 2019-11-23 00:00:00.000 |      1782 |        26548 |     4618163 | M      |          1 |               |                0 |       99 | Faktura   |
|          6314467 | 2019-10-31 00:00:00.000 |      1782 |        26566 |     8426271 | M      |          1 |               |                0 |       99 | Kort      |
|          6310328 | 2019-10-25 00:00:00.000 |      1782 |        27021 |     9107454 | M      |          1 |               |                0 |       99 | Kort      |
|          6311703 | 2019-10-07 00:00:00.000 |      1782 |        26836 |     3792701 | M      |          1 |               |                0 |       99 | Faktura   |
|          6312262 | 2019-10-05 00:00:00.000 |      1782 |        27011 |     9107452 | M      |          1 |               |                0 |       99 | Faktura   |
|          6313316 | 2019-10-05 00:00:00.000 |      1782 |        27011 |     8426271 | M      |          1 |               |                0 |       99 | Faktura   |
|          6314215 | 2019-10-05 00:00:00.000 |      1782 |        26582 |     2626045 | M      |          1 |               |                0 |       99 | Kort      |
|          6319178 | 2019-10-01 00:00:00.000 |      1782 |        26844 |     8929031 | M      |          1 |               |                0 |       99 | Kort      |

 


tables: name: Articles
data: Articles.csv
name: CustomerClub
data: CustomerClub.csv
name: Manufacturer
data: Manufacturer.csv
name: Stores
data: Stores.csv
name: Transactions
data: Transactions.csv
label: Transactions
ArticleID
Articles
ArticleID
Articles
ManufacturerID
Manufacturer
ManufacturerID
Transactions
CustomerID
CustomerClub
CustomerID
Transactions
StoreID
Stores
StoreID
output: {
    "joins": [
        {
            "from_table": "Transactions",
            "from_column": "ArticleID",
            "to_table": "Articles",
            "to_column": "ArticleID"
        },
        {
            "from_table": "Articles",
            "from_column": "ManufacturerID",
            "to_table": "Manufacturer",
            "to_column": "ManufacturerID"
        },
        {
            "from_table": "Transactions",
            "from_column": "CustomerID",
            "to_table": "CustomerClub",
            "to_column": "CustomerID"
        },
        {
            "from_table": "Transactions",
            "from_column": "StoreID",
            "to_table": "Stores",
            "to_column": "StoreID"
        }
    ]
}