Basics on Data Bases and Data Quality Data & Knowledge models and techniques/ Dgital knowledgeware/From data to insights/Business analytics Data Quality

Evaluating the Business Impacts of Poor Data Quality

Loshin analizza la relazione tra processi di business e scarsa qualità dei dati


Establishing a business case for introducing and developing a data quality management program is often predicated on the extent to which data quality issues impact the organization and the return on the investment in data quality improvement. Today, most organizations use data in two ways: transactional/operational use (“running the business”), and analytic use (“improving the business”).

When the results of analysis permeate the operational use, the organization can exploit discovered knowledge to optimize along a number of value drive dimensions. Both usage scenarios rely on high quality information, suggesting the need for processes to ensure that data is of sufficient quality to meet all the business needs. Therefore, it is of great value to any enterprise risk management program to incorporate a program that includes processes for assessing, measuring, reporting, reacting to, and controlling different aspects of risks associated with poor data quality.

Per approfondire si veda anche il libro  

C. Batini e M. Scannapieco – Data and Information Quality, Springer, 2001.