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Siebel Data Quality Administration Guide > Siebel Data Quality Universal Connector > Data Cleansing and Data Matching with SDQ Universal Connector >
Typical Data Cleansing Operations Performed by the SDQ Universal Connector
Data cleansing can fix inaccurate and inconsistent data for new or modified account, contact, and prospect records, as described in Table 6. NOTE: Data cleansing can be done only with the Siebel Data Quality (SDQ) Universal Connector, not with the Siebel Data Quality (SDQ) Matching Server.
Table 6. Data Cleansing Operations
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Address correction |
Address correction updates the fields on an address record with values from a certified external source, typically a directory of addresses from a national postal service or other organization. Typically address correction modifies the following fields: Street Address City State/Province Postal Code/ZIP Code For example, for recognized U.S. addresses, the application reconciles the Address fields with their corresponding ZIP + 4 postal codes. It then stores these fields in standard 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 |
Capitalization standardizes name and address data. For example, a company name and address is converted into title case (Siebel Systems) or all caps (SIEBEL SYSTEMS). |
Standardization |
Standardization sets the abbreviations and other formatting of a name or address record. For example, Siebel Systems, Incorporated becomes Siebel Systems, Inc. and IBM Corporation becomes IBM Corp. Typically, standardization operates on different sets of fields for account, contact, and prospect records. Account records. Typical fields are Account Name and Site fields for account records. Contact and prospect records. Typical fields are First Name, Middle Name, Last Name, and Job Title for these records. |
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