1. Data Quality for Oracle Customer Hub Guide
  2. Data Cleansing

Data Cleansing

Data cleansing is used to correct data and make data consistent in new or modified customer records and typically consists of the following functions:

  • Automatic population of fields in addresses. If a user enters valid values for Zip Code, City, and Country, data quality automatically supplies a State field value. Likewise, if a user enters valid values for City, State, and Country, data quality automatically supplies a Zip Code value.

  • Address correction. Data quality stores street address, city, state, and postal code information in a uniform and consistent format, as mandated by U.S. postal requirements. For recognized U.S. addresses, address correction provides ZIP+4 data correction and stores the data in certified U.S. Postal Service format. For example, 100 South Main Street, San Mateo, CA 94401 becomes 100 S. Main St., San Mateo, CA 94401-3256.

  • Capitalization. Based on configuration, data quality converts fields for account, contact, prospect, and address to mixed case, all lowercase, or all uppercase.

  • Standardization. Data quality ensures account, contact, and prospect information is stored in a uniform and consistent format. For example, IBM Corporation becomes IBM Corp.

Data cleansing is supported for the Account, Business Address, Contact, and List Mgmt Prospective Contact business components. For each business component, particular fields are used in data cleansing and this set of fields is configurable.