Data Quality Management

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Data Quality Management Issues and Challenges
Today's global trading environment is plagued by inconsistent, inaccurate, and untimely data. Disparate information systems and data formats are central to the issue. Message formats, terminology, and codes may differ across countries, companies and agencies.

Normalizing data across multiple parties can be daunting, but necessary to avoid miscommunications and costly mistakes. Shippers need a data quality program that delivers information accurately, with results that can be trusted by users.

Data Quality Management

How Amber Road Can Help
A data network is only as good as the quality of the information that gets exchanged. The data quality management (DQM) features of our network offer best-in-class information accuracy for all messages exchanged between trading partners.

Advanced database technologies and validation rules form the foundation for DQM. By validating messages in three dimensions - completeness, timeliness, and accuracy - DQM gives you the confidence that the messages received from other entities are mapping precisely to the system's own syntax for the highest quality of information.

The data quality engine processes hundreds of business rules to evaluate each message before it is posted to the operational data store. This ensures that it is defined correctly for format and syntax. The data store then translates the messages into a standard format (e.g., time, product and location codes) and sequences them with other messages.

Our DQM engine delivers the highest level of data quality so that your team can make vital, time-sensitive decisions to reduce inventory and transportation costs.