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Required Feature Group Types

To train a model under this use case, you will need to create feature groups of the following type(s):

Feature Group Type	API Configuration Name	Required	Description
Historic Sales Data	TIMESERIES	True	This dataset corresponds to the historical sales data based on the dimension you want to forecast in (e.g., sales rep, team, region, etc.).
Item Attributes	ITEM_ATTRIBUTES		This dataset corresponds to all the attributes or meta-data that you have about the dimension you are forecasting in (e.g attributes about sales rep, team, region, etc).

Note: Once you upload the datasets under each Feature Group Type that comply with their respective required schemas, you will need to create Machine learning (ML) features that would be used to train your ML model(s). We use the term, "Feature Group" for a group of ML features (dataset columns) under a specific Feature Group Type. Our system support extensible schemas that enables you to provide any number of additional columns/features that you think are relevant to that Feature Group Type.

Feature Group: Historic Sales Data

This dataset corresponds to the historical sales data based on the dimension you want to forecast in (e.g., sales rep, team, region, etc.).

Feature Mapping	Feature Type	Required	Description
ITEM_ID	categorical	Y	This is the unique identifier for the sales rep, team, product or region whose sales you want to forecast. You can slice your historic sales data with respect to any dimension (e.g. sales rep, team, region etc.) and then create a dataset based on that dimension.
SALES	numerical	Y	The sales count/dollar amount/ or other numerical metric for the item.
DATE	timestamp	Y	Date (day, year or month) that corresponds to the sales value.
FUTURE		N	Known values ahead of time (e.g., State Holidays, National Holidays, etc.) that can be easily included in the training dataset.

Feature Group: Item Attributes

This dataset corresponds to all the attributes or meta-data that you have about the dimension you are forecasting in (e.g attributes about sales rep, team, region, etc).

Feature Mapping	Feature Type	Required	Description
ITEM_ID	categorical	Y	The unique identifier for the sales rep, team, product or region whose sales you want to forecast.
(Attribute Columns)		Y	Any relevant attribute about the item. For sales regions, it may be attributes such as market size of the region, the number of reps in a particular region, etc. We suggest providing at least 5-6 attributes per lead and up to a maximum of 1000 attributes.