findIT S2 web application
findIT S2 is a fully integrated, real-time, web application for:
- Entry of postally correct US addresses in 40% or less of the keystrokes typically required.
- Real-time duplicate prevention where the name is already on the database.
- 'Fuzzy lookup' of individual and company names to find records that have been keyed wrongly or inconsistently.
- Establishing a Single Customer View across multiple data sources.
findIT S2 additionally provides data enhancement functions within any customer data driven application to help businesses of all sizes to improve data quality at the point of entry. Implementation is extremely simple for database administrators or anyone with the right authority and database configuration knowledge – no programming skills are required.
findIT S2 is unique in that it’s designed to be embedded or integrated into the frontend application and reside between the data entry process and database.
findIT S2’s user interface simplifies and accelerates the data entry process by reducing keystrokes required while reporting potential duplicates already on the database to the user. The user interface is so intuitive; there is almost no user training or familiarization required. Deploy and go.
For US addresses, reference to the USPS database ensures that addresses are entered completely and accurately, and typically in only 12-15 keystrokes. The data quality engine can append further reference data, standardize and correct input, and post the information back to the underlying database, and can be easily configured to run in interactive, real-time, or unattended modes.
Additionally findIT S2 can connect to multiple data sources to enhance data or to identify potential duplicates or existing accounts in other databases or suppression files – making it ideal for e-Commerce and Red Flag environments to provide an immediate alert for existing accounts or for fraud detection.
Because findIT S2 removes the issue of latency between record input and action, your data doesn’t suffer the downstream effects of today’s traditional data quality applications processing.
