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Three Steps to Ensuring Enterprise Data Quality Computers Articles | March 12 Jakub Voracek Olympics Jersey , 2011
Most businesses today are heavily dependent on data, and quite often, they flow in through a multitude of channels, ranging from consumer surveys, polls Vladimir Sobotka Olympics Jersey , and sales to administration and accou...


Most businesses today are heavily dependent on data, and quite often, they flow in through a multitude of channels, ranging from consumer surveys, polls Tomas Plekanec Olympics Jersey , and sales to administration and accounting departments. This data is absolutely crucial and in many ways, can shape the future success and failure of the company. However, information is completely useless if it is inaccurate, inconsistent or incomplete. In fact, a recent article in a leading magazine argues that businesses looking to beef up their corporate governance David Pastrnak Olympics Jersey , risk management and regulatory compliance standards should focus on their enterprise data quality standards.

Obviously the solution to all this is Enterprise Data Quality Management (EDQM). However, this is easier said than done, as this is not something that can be implemented quickly or as a short-term stopgap measure. It requires a deep understanding of both how data flows through a business and consequently, where data quality management measures need to be implemented to be the most effective. Once this understanding is complete, the process of EDQM can begin.

* Ensuring the inflow of high quality data ? Information flows into a company through multiple channels. Some can be controlled Ondrej Palat Olympics Jersey , for example when legacy data transferred to a new system; they needs to be r-engineered to match current standards. At points where this inflow cannot be controlled, for example the internet, filters need to be in place that ensure its correctness as much as possible, as well as match it to corporate standards.

* Maintaining high-quality data in the company information system ? The creation of an internal group that oversees the maintenance of corporate data goes a long way towards maintaining quality. Also important is to perform regular quality audits on particularly critical information pools.

* Maintaining information integrity in step with the latest business strategies of the company ? often data that is accurate ceases to be so with new acquisitions and company mergers. That information needs to be changed, eliminated or revised.

EDQM is all about maintaining the correctness and accuracy of company information. And one of the most important steps in tightening enterprise data quality standards is to invest in high quality EDQM solutions.




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