Markdown Module Dataset

markdown module allows to plan and execute price reductions with respect to the stock levels, set timeframe, and expected demand there are two different processes for the optimal discount calculation that require slightly different data inputs short term expiration markdown a specialized option for near real time calculation of optimal discounts for fresh assortment with short shelf life to work optimally it needs to work with stock data per batch = group of items with the same sell by date long term markdown a more general option for other types of markdowns (clearances) – seasonal, end of life, overstock this process works with total stock regardless of batches primary keys of the tables are highlighted in bold stores table extension the standard stores file shall be extended with two additional columns specifying the warehouses assigned to each store column data type description warehouse id string warehouse identifier warehouse name string name of the warehouse markdown batches the file contains information about remaining stock and product batches column data type description product id string product identifier warehouse id string warehouse identifier batch id string batch identifier expiration date date expiration date quantity decimal(2) stock remaining quantity optional columns column data type description data checks quantity must not be negative the expiration date must always be in the future expiration product markdown the file contains information about each product’s declared shelf life and defines the number of days before expiration when the sellout process should begin column data type description product id string product identifier day sale rule integer the minimum number of days before which it is necessary to apply a markdown to a product (in days) shelf life integer declared shelf life of the product (in days) data checks day sale rule and shelf life must be greater than 0 shelf life must always be greater than day sale rule other options for export add the columns day sale rule and shelf life as new fields in the products file sales the standard sales file will be extended with one additional column to indicate the product batch if the transaction was a markdown column data type description batch id string batch identifier write offs this table contains information about write offs for write offs data, we distinguish between two types historical data – one time export of the entire two year write offs history into a single file named write offs history csv daily incremental data – export write offs for the last n days (minimum 1, maximum 30) into the file writeoffs csv column data type description product id string product identifier warehouse id string warehouse identifier date date date when the product was written off quantity decimal(2) quantity of written off product optional columns column data type description reason string reason for write offs (e g , expired products, damaged goods) data checks quantity must not be negative the date must be in the past