By Elliot King
We have all read the statistics about the real costs that poor data quality represents. And intuitively, we know that bad data is, well, bad. But, in many cases, bad data is more than just bad for business. Increasingly, good data is required by law.
We have all read the statistics about the real costs that poor data quality represents. And intuitively, we know that bad data is, well, bad. But, in many cases, bad data is more than just bad for business. Increasingly, good data is required by law.
In 2001, the U.S. Congress added
two lines to its major appropriations act that required that the Office of
Management and Budget "provide policy and procedural guidance to Federal
agencies for ensuring and maximizing the quality, objectivity, utility, and
integrity of information (including statistical information) disseminated by
Federal agencies." These two lines have come to be known as the Data Quality Act
(DQA) or the Information Quality Act.
While the DQA applied to federal agencies, it also put a marker in the ground. Regulatory agencies could demand that data given to them meet criteria set by the Congress. Government data had to be accurate, objective and have integrity as a matter of law.
The same notion has spread to corporate America and other specific industries. In one of the most high profile examples, the Dodd-Frank Wall Street Reform and Consumer Protection Act passed in the wake of the financial meltdown of 2008 established the Office of Financial Research with a mandate to improve the quality of financial data accessible to regulators.
One of the primary challenges for financial institutions is to insure that the information they supply to regulators is consistent across all their divisions. Companies are also going to be able to track data flows and usage and develop chains of custody that can be audited. The net result should be that all users of the data will see consistent information. And that may not be easy when data is siloed in different operating entities, which is often the case in those too-big-to-fail financial behemoths.
The regulatory pressure for data quality is being felt elsewhere as well. The American Health Information Management Association, which promotes the technological advancement of health information management systems, has noted that for electronic health records (EHR) to have the positive impact on overall health care that their proponents anticipate, data quality can no longer be a reactive process based on auditing but must be proactively focused on data capture. Standards to ensure that result will be built into the requirements for EHRs.
While many folks in IT chafe at government regulations. However, the Federal government often has been a leader in IT innovation. Think about the Internet. Federal IT initiatives have also been inept--think about the FBI case management system or the Air Traffic Control system. While burdensome, the regulatory demand for higher quality data could easily have a positive ripple effect that will spread widely.
http://blog.melissadata.com/data-quality-authority/2012/04/sometimes-data-quality-is-the-law.html
While the DQA applied to federal agencies, it also put a marker in the ground. Regulatory agencies could demand that data given to them meet criteria set by the Congress. Government data had to be accurate, objective and have integrity as a matter of law.
The same notion has spread to corporate America and other specific industries. In one of the most high profile examples, the Dodd-Frank Wall Street Reform and Consumer Protection Act passed in the wake of the financial meltdown of 2008 established the Office of Financial Research with a mandate to improve the quality of financial data accessible to regulators.
One of the primary challenges for financial institutions is to insure that the information they supply to regulators is consistent across all their divisions. Companies are also going to be able to track data flows and usage and develop chains of custody that can be audited. The net result should be that all users of the data will see consistent information. And that may not be easy when data is siloed in different operating entities, which is often the case in those too-big-to-fail financial behemoths.
The regulatory pressure for data quality is being felt elsewhere as well. The American Health Information Management Association, which promotes the technological advancement of health information management systems, has noted that for electronic health records (EHR) to have the positive impact on overall health care that their proponents anticipate, data quality can no longer be a reactive process based on auditing but must be proactively focused on data capture. Standards to ensure that result will be built into the requirements for EHRs.
While many folks in IT chafe at government regulations. However, the Federal government often has been a leader in IT innovation. Think about the Internet. Federal IT initiatives have also been inept--think about the FBI case management system or the Air Traffic Control system. While burdensome, the regulatory demand for higher quality data could easily have a positive ripple effect that will spread widely.
http://blog.melissadata.com/data-quality-authority/2012/04/sometimes-data-quality-is-the-law.html