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Commodity Coding: Code It or Buy (Too Much of) It
sponsored by DataFlux Corporation

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).

Buy or build have always been two alternatives to consider in the world of information technology. Some choose to always buy, some always build and some choose to do both where it makes sense for the organization. The answer for your organization depends on your needs, including how much control you want to have over the commodity classification process.

This paper will present you with all the information needed to make an educated decision on whether to commodity coding is right for your organization and it will help with choosing the commodity coding that fits your company.

(THIS RESOURCE IS NO LONGER AVAILABLE.)
 
Available Resources from DataFlux Corporation
sponsored by DataFlux Corporation

PODCAST - In this 12 minute podcast, get expert advice for successfully leading data quality management initiatives. Find out more about data quality program planning, required skill sets and common challenges.
Posted: 25 Jan 2010 | Premiered: 25 Jan 2010


sponsored by DataFlux Corporation

WHITE PAPER - This paper explores how a rigorous data quality program is now a business imperative rather than a luxury. Implemented correctly, it not only gives organizations the agility to better ride out the current recession but also raises their competitiveness when the economy recovers.
Posted: 22 Jan 2010 | Published: 22 Jan 2010


sponsored by DataFlux Corporation

WHITE PAPER - In the summer of 2009, DataFlux conducted a survey to understand data management trends in the financial services industry. The research examined how this industry is approaching managing its data, the breadth and depth of data governance in this sector, what motivates data management strategies, and more.
Posted: 22 Jan 2010 | Published: 22 Jan 2010


sponsored by DataFlux Corporation

WHITE PAPER - This paper provides practical advice that will help the reader understand the pivotal role data quality technology must play in a data migration and describes five distinct implementations of data quality technology in detail.
Posted: 22 Jan 2010 | Published: 22 Jan 2010


sponsored by DataFlux Corporation

WHITE PAPER - This paper reviews aspects of cost reduction and examines some typical financial accounting expense categories. This paper also looks at how data quality services can be applied in those examples to reduce expenses, and examines the potential for applying data quality management as a way to manage and reduce organizational expenses.
Posted: 22 Jan 2010 | Published: 22 Jan 2010


sponsored by DataFlux Corporation

WHITE PAPER - This paper examines the impact of unreliable data on retail banks. Defining the requirements needed to guarantee data reliability in retail banking, it offers a practical approach to creating and governing that data, and shows how you can get started in making trusted data available to improve marketing, customer service, risk management and more.
Posted: 04 Nov 2009 | Published: 02 Nov 2009


sponsored by DataFlux Corporation

WHITE PAPER - Only when data is trusted can it be used in confidence in all insurance operational and analytical process activities. This paper examines the impact of unreliable data on insurance companies. It then defines the requirements needed to guarantee data reliability in insurance and offers a practical approach to creating and governing that data.
Posted: 04 Nov 2009 | Published: 02 Nov 2009


sponsored by DataFlux Corporation

WHITE PAPER - Operational data governance is the process of evaluating data to see if data effectively satisfies the organization's business needs. This is measured with a "data quality scorecard", a management tool for monitoring organizational performance.
Posted: 10 Jun 2008 | Published: 06 Jun 2008




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