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One of the most bedeviling aspects of data management is product data. Unlike customer data, which has a few, relatively uniform attributes (name, address, birth date), product data can vary widely across industries and even within a company itself. Recently, organizations have turned to commodity classification or coding techniques to resolve these problems. Most coding schemes come from the need to categorize products and services from a data management perspective. These codes are rooted in systems that allow the manufacturer, retailer or distributor to systematically track and manage the production and inventory of the product or service.
The types of commodity classification taxonomies run the gamut, often providing hierarchy information to handle a variety of products, materials and services. Examples include:
Before talking about the management of commodity data, a definition of commodity is in order. Simply put, a commodity is a product that is in demand and is the same no matter who produces it. There is no difference across the market in a commodity product. This definition can be applied to crude oil, coal, salt, sugar, gold and silver. Commoditization occurs when a product (or a service) loses market differentiation. Generic pharmaceuticals, computer chips, and other electronic components also fall into this category.
So, commodity data is data that can be coded (and categorized) the same across industries, countries and organizations. For these products, a taxonomy is very useful. Taxonomy is the practice of classification of products, services or basically anything usually in a hierarchy of codes. The hierarchy allows for “drill-down” and summarizations at higher levels of the hierarchy (perfect for business intelligence). A sample taxonomy could be applied to motorized vehicles. A car is a subtype of a vehicle, but not every vehicle is car. There are trucks, SUVs, tractors and ATVs as well as passenger vehicles.
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