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: CustomerClassificationTable
| Classification Group   |   Min |   Max |
|:-----------------------|------:|------:|
| Top Customer           |     1 |     5 |
| Medium Customer        |     6 |    20 |
| Bad Customer           |    20 | 10000 |


Table: Datestable
| Date                    |   Year |   QuarterOfYear |   MonthOfYear |   DayOfMonth |   DateInt | MonthName   | MonthInCalendar   | QuarterInCalendar   |   DayInWeek | DayOfWeekName   | WeekEnding              |   Week Number |   MonthnYear |   QuarternYear |   ShortYear | FY   |
|:------------------------|-------:|----------------:|--------------:|-------------:|----------:|:------------|:------------------|:--------------------|------------:|:----------------|:------------------------|--------------:|-------------:|---------------:|------------:|:-----|
| 2017-07-01 00:00:00.000 |   2017 |               3 |             7 |            1 |  20170701 | Juli        | Jul 2017          | Q3 2017             |           5 | Samstag         | 2017-07-02 00:00:00.000 |            27 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-02 00:00:00.000 |   2017 |               3 |             7 |            2 |  20170702 | Juli        | Jul 2017          | Q3 2017             |           6 | Sonntag         | 2017-07-02 00:00:00.000 |            27 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-03 00:00:00.000 |   2017 |               3 |             7 |            3 |  20170703 | Juli        | Jul 2017          | Q3 2017             |           0 | Montag          | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-04 00:00:00.000 |   2017 |               3 |             7 |            4 |  20170704 | Juli        | Jul 2017          | Q3 2017             |           1 | Dienstag        | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-05 00:00:00.000 |   2017 |               3 |             7 |            5 |  20170705 | Juli        | Jul 2017          | Q3 2017             |           2 | Mittwoch        | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-06 00:00:00.000 |   2017 |               3 |             7 |            6 |  20170706 | Juli        | Jul 2017          | Q3 2017             |           3 | Donnerstag      | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-07 00:00:00.000 |   2017 |               3 |             7 |            7 |  20170707 | Juli        | Jul 2017          | Q3 2017             |           4 | Freitag         | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-08 00:00:00.000 |   2017 |               3 |             7 |            8 |  20170708 | Juli        | Jul 2017          | Q3 2017             |           5 | Samstag         | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-09 00:00:00.000 |   2017 |               3 |             7 |            9 |  20170709 | Juli        | Jul 2017          | Q3 2017             |           6 | Sonntag         | 2017-07-09 00:00:00.000 |            28 |     20170700 |       20170300 |          17 | FY18 |
| 2017-07-10 00:00:00.000 |   2017 |               3 |             7 |           10 |  20170710 | Juli        | Jul 2017          | Q3 2017             |           0 | Montag          | 2017-07-16 00:00:00.000 |            29 |     20170700 |       20170300 |          17 | FY18 |


Table: Demandchange
|   Demandchange |
|---------------:|
|          -0.5  |
|          -0.45 |
|          -0.4  |
|          -0.35 |
|          -0.3  |
|          -0.25 |
|          -0.2  |
|          -0.15 |
|          -0.1  |
|          -0.05 |


Table: Employeestable
|   EmployeeID | Employee Name   | Employee Surname   | OfficeCountry   | Office Team   |
|-------------:|:----------------|:-------------------|:----------------|:--------------|
|            1 | Nancy           | Davolio            | USA             | Team Fuller   |
|            2 | Andrew          | Fuller             | USA             | Team Fuller   |
|            3 | Janet           | Leverling          | USA             | Team Fuller   |
|            4 | Margaret        | Peacock            | USA             | Team Fuller   |
|            5 | Steven          | Buchanan           | UK              | Team Fuller   |
|            6 | Michael         | Suyama             | UK              | Team Buchanan |
|            7 | Robert          | King               | UK              | Team Buchanan |
|            8 | Laura           | Callahan           | USA             | Team Fuller   |
|            9 | Anne            | Dodsworth          | UK              | Team Buchanan |


Table: Pricechange
|   Pricechange |
|--------------:|
|          0    |
|          0.05 |
|          0.1  |
|          0.15 |
|          0.2  |
|          0.25 |
|          0.3  |
|          0.35 |
|          0.4  |
|          0.45 |


Table: Rankingparameter
|   Rankingparameter |
|-------------------:|
|                  1 |
|                  2 |
|                  3 |
|                  4 |
|                  5 |
|                  6 |
|                  7 |
|                  8 |


Table: Salestable
|   OrderID | CustomerID   |   ProductID |   EmployeeID | OrderDate               | ShipDate                | ShipMode   |   Sales |   Standardprice |   SellingPrice |   Amount |   Discount | ProductName            |   SupplierID |   PurchasingPrice | CustomerCompany            | CustomerName       |   CustomerZIPCode | Region   | CustomerCountry   | Category   |
|----------:|:-------------|------------:|-------------:|:------------------------|:------------------------|:-----------|--------:|----------------:|---------------:|---------:|-----------:|:-----------------------|-------------:|------------------:|:---------------------------|:-------------------|------------------:|:---------|:------------------|:-----------|
|     10271 | SPLIR        |          33 |            6 | 2017-08-01 00:00:00.000 | 2017-08-06 00:00:00.000 | DHL        |    60   |            2.5  |           2.5  |       24 |          0 | Geitost                |           15 |           1.39857 | Split Rail Beer & Ale      | Art Braunschweiger |             82520 | America  | USA               | Cheese     |
|     10272 | RATTC        |          20 |            6 | 2017-08-02 00:00:00.000 | 2017-08-06 00:00:00.000 | DHL        |   486   |           81    |          81    |        6 |          0 | Sir Rodney's Marmalade |            8 |          57.8155  | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Deserts    |
|     10272 | RATTC        |          31 |            6 | 2017-08-02 00:00:00.000 | 2017-08-06 00:00:00.000 | DHL        |   500   |           12.5  |          12.5  |       40 |          0 | Gorgonzola Telino      |           14 |           8.921   | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Cheese     |
|     10272 | RATTC        |          72 |            6 | 2017-08-02 00:00:00.000 | 2017-08-12 00:00:00.000 | DHL        |   835.2 |           34.8  |          34.8  |       24 |          0 | Mozzarella di Giovanni |           14 |          14.9028  | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Cheese     |
|     10294 | RATTC        |           1 |            4 | 2017-08-30 00:00:00.000 | 2017-09-05 00:00:00.000 | DHL        |   324   |           18    |          18    |       18 |          0 | Chai                   |            1 |           9.94128 | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Drinks     |
|     10294 | RATTC        |          17 |            4 | 2017-08-30 00:00:00.000 | 2017-09-05 00:00:00.000 | DHL        |   585   |           39    |          39    |       15 |          0 | Alice Mutton           |            7 |          24.7749  | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Meat       |
|     10294 | RATTC        |          43 |            4 | 2017-08-30 00:00:00.000 | 2017-09-05 00:00:00.000 | DHL        |   690   |           46    |          46    |       15 |          0 | Ipoh Coffee            |           20 |          33.7197  | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Drinks     |
|     10294 | RATTC        |          60 |            4 | 2017-08-30 00:00:00.000 | 2017-09-05 00:00:00.000 | DHL        |   714   |           34    |          34    |       21 |          0 | Camembert Pierrot      |           28 |          17.1861  | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Cheese     |
|     10294 | RATTC        |          75 |            4 | 2017-08-30 00:00:00.000 | 2017-09-10 00:00:00.000 | DHL        |    46.5 |            7.75 |           7.75 |        6 |          0 | Rhönbräu Klosterbier   |           12 |           3.84957 | Rattlesnake Canyon Grocery | Paula Wilson       |             87110 | America  | USA               | Drinks     |
|     10307 | LONEP        |          62 |            2 | 2017-09-17 00:00:00.000 | 2017-09-25 00:00:00.000 | DHL        |   493   |           49.3  |          49.3  |       10 |          0 | Tarte au sucre         |           29 |          34.8681  | Lonesome Pine Restaurant   | Fran Wilson        |             97219 | America  | USA               | Deserts    |


Table: Suppliertable
|   Supplier-ID | Suppliername                       | Country   |
|--------------:|:-----------------------------------|:----------|
|             1 | Exotic Liquids                     | UK        |
|             2 | New Orleans Cajun Delights         | USA       |
|             3 | Grandma Kelly's Homestead          | USA       |
|             4 | Tokyo Traders                      | Japan     |
|             5 | Cooperativa de Quesos 'Las Cabras' | Spain     |
|             6 | Mayumi's                           | Japan     |
|             7 | Pavlova, Ltd.                      | Australia |
|             8 | Specialty Biscuits, Ltd.           | UK        |
|             9 | PB Knäckebröd AB                   | Sweden    |
|            10 | Refrescos Americanas LTDA          | Brazil    |

 


tables: name: CustomerClassificationTable
data: CustomerClassificationTable.csv
name: Datestable
data: Datestable.csv
name: Demandchange
data: Demandchange.csv
name: Employeestable
data: Employeestable.csv
name: Pricechange
data: Pricechange.csv
name: Rankingparameter
data: Rankingparameter.csv
name: Salestable
data: Salestable.csv
name: Suppliertable
data: Suppliertable.csv
label: Salestable
EmployeeID
Employeestable
EmployeeID
Salestable
SupplierID
Suppliertable
Supplier-ID
Salestable
OrderDate
Datestable
Date
output: {
    "joins": [
        {
            "from_table": "Salestable",
            "from_column": "EmployeeID",
            "to_table": "Employeestable",
            "to_column": "EmployeeID"
        },
        {
            "from_table": "Salestable",
            "from_column": "SupplierID",
            "to_table": "Suppliertable",
            "to_column": "Supplier-ID"
        },
        {
            "from_table": "Salestable",
            "from_column": "OrderDate",
            "to_table": "Datestable",
            "to_column": "Date"
        }
    ]
}