1.Extract, normalize, and standardize your data across multiple inputs and formats.

2.Normalize all your information – including business and individual data, structured and unstructured.

3.Precisely applies supervised machine learning neural network-based techniques to understand the structure and variations of different types of  information and parses data automatically.

4.Standardize, match, deduplicate, analyze, and consolidate customer information. Understanding individual and business names worldwide is essential to creating an engaging personalized experience while reducing risk and unnecessary cost.

5.A comprehensive database of family names, given names and variants, ethnicity and gender codes (including Arabic and Asian languages) will enable you to easily identify typing errors, alternate spellings and abbreviations in native and Romanized forms (e.g. in Japan, China and Korea).

6.Evaluate records against a set of conditions to determine if they require manual review

Write the exception records to the exception repository for review

7.Reprocess exception records already corrected by a data steward

8.Use the business steward portal – a dashboard of statistics and charts on a browser-based tool

9.Use the outcome of your exception handling to fine tune your  Smart Quality matching  (applied machine learning for better accuracy at lower costs)