Data Quality Management

Experian Data Quality provides a comprehensive data management solution that helps customers keep the customer's records accurate, reduce errors, and avoid extra costs associated with bad data. Let's learn how we can help you

Eliminate duplicate entries and connect data across various channels and systems to achieve gold records

Confirm fixed phone number and mobile phone number to improve phone marketing campaign and comply with federal regulations

Improve the efficiency of targeted marketing campaigns by better understanding customer demographics, behavior and lifestyle attributes

Are you ready to take the next step in data quality maturity? We will help you clean up, standardize and strengthen your data to ensure you take full advantage of your information

First, excellent data quality management will lay the foundation for every business initiative. Expired or unreliable data can lead to errors and errors. The data quality control program establishes a framework for providing and enforcing data quality rules for all departments within the organization. Secondly, as accurate and up-to-date data clearly shows the company's daily work, I am confident in upstream and downstream applications that use all data. Data quality control also reduces unnecessary costs. Poor quality may result in costly mistakes or omissions such as order loss or expenditure. Data Quality Management builds an information infrastructure that can understand organization and cost by firmly acquiring data.

To achieve high data quality status, the organization needs to implement integrated data quality management (TDQM). Various industries with various purposes and environments can develop more specific and customized data quality control procedures to meet their needs. However, regardless of the difference, the organization believes that it is necessary to follow certain procedures to successfully implement the executable TDQM. Please use the Internet and online transactions. E-commerce organizations interact more closely with the environment, increasing the complexity of data quality. Therefore, the e-commerce organization needs to establish a data quality strategy and implementation method suitable for e-commerce conversion method (Segev & Wang, 2001).