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Data profiling is a technique used to examine data for different purposes like determining accuracy and completeness. This process examines a data source such as a database to uncover the erroneous areas in data organization. Deployment of this technique improves data quality.
Data profiling is also referred to as data discovery.
Data profiling is the method of examining the data available in a data source and collecting statistics and information about that data. Such statistics help to identify the use and data quality of metadata. This method is widely used in enterprise data warehousing.
Data profiling clarifies the structure, relationship, content and derivation rules of data, which aid in the understanding of anomalies within metadata. Data profiling uses different kinds of descriptive statistics including mean, minimum, maximum, percentile, frequency and other aggregates such as count and sum. The additional metadata information obtained during profiling is data type, length, discrete values, uniqueness and abstract type recognition.