DATA QUALITY AND STANDARDIZATION

The average financial impact of poor data quality on organizations is estimated to be at $14.2 million per year costing businesses at least 30% of revenues. Furthermore, nearly one third of analysts spend more than 40 percent of their time vetting and validating their analytics data before it can be used for strategic decision-making.

Bottomline: bad data is bad for business.

Our data quality and fuzzy matching solutions automates the processing and cleansing of unstructured and semi-structured data, eliminating duplicate customer, employee and product records and yielding efficient and accurate business outcomes.