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Data enrichment is a common phrase that represents procedures used to enhance, refine or otherwise improve raw data. This concept and other identical ideas give rise to making data a useful resource for almost any contemporary business or business. It also reveals the common crucial of proactively using this data in various ways. Data augmentation can range from something as simple as adding a missing postcode, to augmenting records with demographic or geographic data based on a name or address match. It’s a simple process, with the value gained far outweighing the effort required.
Although data enrichment can work in many different ways, many of the tools used for this goal involve a refinement of data that might include small errors.
Although data enrichment can work in many different ways, many of the tools used for this goal involve a refinement of data that might include small errors.
common data enrichment process could, for example, correct likely misspellings or typographical errors in a database through the use of precision algorithms. Following this logic, data enrichment tools could also add information to simple data tables.
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Technologies in SAS enable you to enrich data with the following types of information:
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• Geographic: such as postcode, county name, longitude and latitude, and political district
• Behavioral: including purchases, credit risk and preferred communication channels
• Demographic: such as income, marital status, education, age and number of children
• Psychographic: ranging from hobbies and interests to political affiliation
• Census: household and community data
• Behavioral: including purchases, credit risk and preferred communication channels
• Demographic: such as income, marital status, education, age and number of children
• Psychographic: ranging from hobbies and interests to political affiliation
• Census: household and community data
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