Data Schemas
Mantissa leverages two types of historical data: purchase orders and sales orders. In this section, we provide the schema for each type of data.
Sales orders data
In the following table, you can find the schema for the sales orders data. The data must be uploaded via a single csv file, and must have all the columns listed below. Any extra columns will be ignored.
| Column name | Description | Format details | Nullable | Example |
|---|---|---|---|---|
| OrderDateTime | Datetime on which the order is placed. | yyyy-mm-ddThh:MM:ss+hh:MM (timezone is optional) | False | 2022-01-01T00:00:00 |
| DeliveryDateTime | Datetime on which the order is delivered. | yyyy-mm-ddThh:MM:ss+hh:MM (timezone is optional) | True | 2022-01-05T00:00:00 |
| Quantity | Quantity of the item ordered. | Positive number with decimal digits separated by dots | False | 10.3 |
| MeasureUnit | Unit of measure of the quantity ordered. | String | True | kg |
| ItemCode | First-level identifier of the item ordered. | String | False | 1234 |
| ItemClassification | Second-level identifier of the item ordered. | String | True | classification1 |
| ItemFamily | Third-level identifier of the item ordered. | String | True | family1 |
Columns ItemCode, ItemClassification and ItemFamily correspond to aggregation levels item, classification and family, respectively.
If each value in column ItemFamily is NULL, you will not be allowed to ask for a Demand Prediction with family aggregation level (and the same applies to classification aggregation level).
CSV file example
OrderDateTime,DeliveryDateTime,Quantity,MeasureUnit,ItemCode,ItemClassification,ItemFamily
2022-01-01T00:00:00,2022-01-05T00:00:00,10,kg,1234,classification1,family1
2022-01-02T00:00:00,2022-01-06T00:00:00,20,kg,1235,classification1,family1
2022-01-03T00:00:00,2022-01-07T00:00:00,30,kg,1236,classification2,family2
Purchase orders data
In the following table, you can find the schema for the purchase orders data. The data must be uploaded via a single csv file, and must have all the columns listed below. Any extra columns will be ignored.
| Column name | Description | Format details | Nullable | Example |
|---|---|---|---|---|
| OrderDateTime | Datetime on which the order is placed. | yyyy-mm-ddThh:MM:ss+hh:MM (timezone is optional) | False | 2022-01-01T00:00:00 |
| DeliveryDateTime | Datetime on which the order is received. | yyyy-mm-ddThh:MM:ss+hh:MM (timezone is optional) | False | 2022-01-05T00:00:00 |
| Quantity | Quantity of the item ordered. | Positive number with decimal digits separated by dots | False | 10.3 |
| MeasureUnit | Unit of measure of the quantity ordered. | String | True | kg |
| SupplierCode | Identifier of the supplier to whom the order is placed. | String | False | supp1 |
| ItemCode | First-level identifier of the item ordered. | String | False | 1234 |
| ItemClassification | Second-level identifier of the item ordered. | String | True | classification1 |
| ItemFamily | Third-level identifier of the item ordered. | String | True | family1 |
Columns ItemCode, ItemClassification and ItemFamily correspond to aggregation levels item, classification and family, respectively.
If each value in column ItemFamily is NULL, you will not be allowed to ask for a Lead Time Prediction with family aggregation level (and the same applies to classification aggregation level).
CSV file example
OrderDateTime,DeliveryDateTime,Quantity,MeasureUnit,SupplierCode,ItemCode,ItemClassification,ItemFamily
2022-01-01T00:00:00,2022-01-05T00:00:00,10,kg,supp1,1234,classification1,family1
2022-01-02T00:00:00,2022-01-06T00:00:00,20,kg,supp1,1235,classification1,family1
2022-01-03T00:00:00,2022-01-07T00:00:00,30,kg,supp2,1236,classification2,family2