This is material to supplement Warehouse & Distribution Science, a textbook and a graduate course taught at the Georgia Institute of Technology by John J. BARTHOLDI, III and Steven T. HACKMAN. Everyone is welcome to use the book and materials here for educational purposes, so long as the copyrights remain intact. You will find more information and technical details on these topics within the book.

Data-Mining for warehouse activity profiling

Purpose

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Warehouse profiling is a special case of data-mining, which is simply jargon for sifting through historical data for opportunities and insights that might confer advantage. As the name suggests, there is a certain amount of serendipity involved, along with a knowledge of what to look for and how to search most efficiently. It is also important to have the right tools.

The data of most enterprises resides in large relational database management systems, such as Oracle, Informix, Sybase, and others. A database contains a collection of tables, each of which is similar to a spreadsheet in which each row describes some object, such as a sku; and each column describes some attribute of the object, such as its name or weight.

To mine data requires first that you manage large datasets. The main tool you will need is some program that will allow you to query multiple tables and to perform joins, which connect the data in one table with that in another through some common key. The industry-standard way to extract data from a database is via the Structured Query Language (SQL).

Resources

Here is an introduction to the use of relational databases and SQL to examine warehouse activities. This exercise guides you in setting up some basic database tools and it provides you with a clean set of data on which to practice.
Here is a list of all the data for which you should ask if undertaking an independent profiling project.