Data Standardization

Typical Problem Description:
Enterprises depend on accurate data feeding their management reporting systems to understand the relative health of the organization, identify potential risk before negative events occur and optimize business processes. Data with similar meaning and function coming from multiple sources with subtle differences in formatting can cause fallout during processing leading to decreased veracity of management reporting, increased costs from rework, and customer service delays.
Data Standardization use case nice sincera
How NICE solves the problem:
NICE allows companies to implement data standardization across your back office systems. NICE connectors can be quickly built and configured to connect to any data source. Rules are implemented in an intuitive, low/no code user interface allowing coders and non-coders to create and apply customized rules converting data from multiple sources into standard, consistently formatted data. NICE propagates the standardized data back into your operational systems allowing for improved automation of business processes, reduced operational costs, decreased fallout, and faster Time to Revenue.
The Benefit:
Standardizing data across all your enterprise data sources significantly improves the accuracy of your management reports, lowers operational costs by revealing efficiencies previously obscured by bad data, and improves your Time to Revenue by decreasing service provisioning intervals.
Benefits of Data Reconciliation and Cleansing Sincera