Markdown Module Dataset

markdown refers to reducing prices for items that are nearing expiration or need to be sold quickly, even if this requires accepting a lower profit margin each table indicates the column name in the file, the data type, and a description primary keys (unique values) are highlighted in bold 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 stores the standard stores file will 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 stores csv https //d3jwyy9rhyhl55 cloudfront net/v2/4158/contents/osbs4gpnbhkq8wwt/stores csv 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 unit string unit of measurement (kg, pc, ml) optional columns column data type description unit string unit of measurement (kg, pc, ml) batches csv https //d3jwyy9rhyhl55 cloudfront net/v2/4158/contents/p2jvrpkiyizdj1qw/batches csv 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) product expiration csv https //d3jwyy9rhyhl55 cloudfront net/v2/4158/contents/xnepcwve3k76eh4m/product expiration csv 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 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) writeoffs csv https //d3jwyy9rhyhl55 cloudfront net/v2/4158/contents/bt9rl1enoniveknu/writeoffs csv data checks quantity must not be negative the date must be in the past