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- Raw data (sometimes called source data or atomic data) is data that has not been processed for use. A distinction is sometimes made between data and information to the effect that information is the end product of data processing. Raw data that has undergone processing is sometimes referred to as cooked data.

Although raw data has the potential to become "information," it requires selective extraction, organization, and sometimes analysis and formatting for presentation. For example, a point-of-sale terminal (POS terminal) in a busy supermarket collects huge volumes of raw data each day, but that data doesn't yield much information until it is processed. Once processed, the data may indicate the particular items that each customer buys, when they buy them, and at what price. Such information can be further subjected to predictive technology analysis to help the owner plan future marketing campaigns.

As a result of processing, raw data sometimes ends up in a database, which enables the data to become accessible for further processing and analysis in a number of different ways.

Learn more about Data quality techniques and best practices

Best practices for designing and implementing sustainable, long-term data quality programs: Learn best practices for designing and implementing data quality management programs.
Data quality management and governance tutorial: This data quality and governance tutorial introduces best practices and technology considerations for maintaining accurate, current and concise data.
Data quality and governance management quiz: Test your knowledge of data quality and governance management concepts, trends and facts in this short quiz.
Data Quality Management Software Product Directory: Inside this data quality management software product directory you'll find basic information about the major vendors in the data quality market and the products they sell.
Data management industry event and conference calendar: Find listings and dates of upcoming data management industry events, conferences and seminars.
Information assurance: Dependability and security of networked information systems: Learn how information assurance involves efforts from both dependability and security areas of networked information systems.
Data quality and governance management quiz: Test your knowledge of data quality and governance management concepts, trends and facts in this short quiz.
Data quality management and governance tutorial: This data quality and governance tutorial introduces best practices and technology considerations for maintaining accurate, current and concise data.

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16 Feb 2009

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More resources from around the web:

-	Statistics Canada provides a tutorial on Data Processing.

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