Preppin' Data

 Challenge by: Jenny Martin It's the IT department's turn to receive our help this week. Rather than optimising the data for feeding into a data visualisation tool, we're going to think about how to optimally store data. In particular, we're going to be thinking about breaking a dataset down into fact and dimension tables.  In many challenges, we focus on bringing datasets together that have a common ID field. Databases will often follow a star schema, where each dimension is a separate table that can join onto the main fact table. We have received the following desired schema from IT: Input We have one large table to break down into the desired fact and dimension tables: Requirements Input the Data Split out the store name from the OrderID Turn the Return State field into a binary Returned field Create a Sales field Create 3 dimension tables for Store, Customer and Product When assigning IDs, these should be created using the dimension and minimum order date fields so ...