Press Release from January 2009 

• Data Quality Real-Time Services from Uniserv act as a firewall and secure customer data quality immediately on input
• Errors are identified "on the fly", automatically corrected or reported to the user
  
  

Pforzheim, November 2008. Irrespective of the market sector, the success of a company depends on consistently high quality of the stored customer data. In order to guarantee this at all times and not only on a one-off basis, however, it is important to subject data to a permanent quality check in a cycle and to ensure that it is automatically checked, matched, enhanced and, if required, also consolidated immediately on input. Creeping contamination of the database and the resulting softening of an already achieved high data quality level is thereby prevented. This is precisely where the software range of DQ Real-Time Services of the Pforzheim-based Uniserv Gmbh for Data Quality comes into play as it ensures that the Customer Data Quality is safeguarded at the moment of data acquisition. Errors, inconsistencies and uncleanliness can be dependably and error-tolerantly cleared up with a large degree of automation on the basis of sophisticated reference data and extensive knowledge bases by means of a portfolio of international, Unicode-capable solutions such as Address Analysis and Structuring, Postal Validation, Error-Tolerant Search and Duplicate Merging and Purging right up to a Telephone Number Check and Banking Data Validation. As an alternative, the user receives an appropriate message as a starting point for the manual review. In this way, incorrect, out-of-date or incomplete information is prevented from reaching the database to the largest possible extent. A particular advantage: As a result of the application- and platform-independent approach, companies can use the DQ Real-Time Services across applications and sectors to merge data e.g. in SAP® and Oracle® environments, thereby obtaining a consistent view of the respective customer.

Data Quality Firewall against data erosion
If the Data Quality Real-Time Services are consistently used at the points at which data gets into the system, they form a secure firewall on the basis of individual data quality checkpoints. Take e-business as an example: The input of incorrect and/or incomplete data occurs on a daily basis here, since customers and prospective customers normally enter their data themselves - frequently abbreviated, unstructured, completely incorrect or with unintentional typing errors. If the respective data quality checks are not carried out here, the contamination of the database in which the data is entered is the inevitable result.

In addition to a check for completeness and validation against reference data, all the master data entered should be checked against the database to ensure permanent database maintenance and, in particular, to prevent the occurrence of duplicates. This is because the prevention of duplicate or multiple instances of existing addresses is an important condition for guaranteeing a consistent and complete view of customers within applications. Depending on the business model, enhancement with external or internal reference data is also advisable.

Option for additional performance, security and comfort
Extending beyond the large number of standard functional capabilities of the Data Quality Real-Time Services, all the servers can be centrally administered and monitored via the product options Server Control and Database Connector. In addition, automatic synchronisation of the specialised, internal data quality indices with the application data is possible via database triggers - stored procedures, which are immediately executed as soon as an event occurs on the database server. Parallelisation, load distribution and redundancy beyond the computer boundaries are therefore possible, something which provides high scalability and extra security.

The DQ Real-Time Services can be called by all generally used programming languages and have a standard application programming interface (API). The function call-up is therefore always identical, irrespective of the platform (client) on which the application is used, the platform (server) which the respective DQ function uses, or of whether the component is integrated in the application or runs in distributed client/server applications on another computer in the network. In this respect, the services can be seamlessly integrated in a wide variety of IT architectures and be called up from rich clients, application servers or databases.

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