Data profiling is the process of studying and analyzing data to validate it against expected data formats and values. Data profiling has traditionally been the purview of the data warehouse, where it was used against disparate source systems to yield data standardization and unification rules as part of extract, transform and load (ETL) processing. Data profiling for data warehouses is less critical than it is for customer data integration (CDI) hubs.
Data profiling takes on a whole new dimension when used for CDI. CDI involves the use of a centralized, transactional hub, which reconciles, unifies and integrates customer-specific data. Such hubs are more targeted to customer data, thus rendering data profiling narrower in scope. The data profiling is targeted to customer's personally identifiable information, including name, address, phone and email. But the complexity and depth of analysis of these elements increase due to the very nature of this data.
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