Difference between revisions of "Data auditing"

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Data auditing is the process of recording the alteration, addition, or removal of data by an application, database, or other software. Ideally, an application will offer the ability for the [[LIMS]] administrator to choose the desired level of data auditing (all data or specific data) as well as a method to easily alter the auditing level.
{{wikipedia::Data auditing}}
 
==Notes==
Data auditing can be controlled by the application itself or the data repository where the [[data]] is stored (so changes are tracked regardless of the source of the change). It is customary to record the old and new values of the data as well as who made the change and the time of the change.
This article is a direct transclusion of [https://en.wikipedia.org/wiki/Data_auditing the Wikipedia article] and therefore may not meet the same editing standards as LIMSwiki.
 
Data auditing is often required to meet regulatory or client requirements. Audit data are also useful for reporting and trouble-shooting LIMS activity. In some systems, audit data can also be used to revert (or rollback) a group of changes (referred to as a [[transaction]]) intended to be [[atomic]].
 
Data auditing may be performed manually, but such records may not be suitable for compliance and cannot be reported on.
 
The downside to data auditing is that it can consume considerable processing and data storage resources.
 
==References==
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[[Category:Regulatory terms]]
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[[Category:Business and data management]]
[[Category:Quality management]]

Latest revision as of 18:02, 18 September 2022

Data auditing is the process of conducting a data audit to assess how company's data is fit for given purpose. This involves profiling the data and assessing the impact of poor quality data on the organization's performance and profits. It can include the determination of the clarity of the data sources and can be applied in the way banks and rating agencies perform due diligence with regard to the treatment of raw data given by firms, particularly the identification of faulty data.[1]

Data auditing can also refer to the audit of a system to determine its efficacy in performing its function. For instance, it can entail the evaluation of the information systems of the IT departments to determine whether they are effective in protecting the integrity of critical data.[2] As an auditing tool, it can detect fraud, intrusions, and other security problems.[3]

References

  1. ^ Kolb, Robert W. (2010-09-09). Lessons from the Financial Crisis: Causes, Consequences, and Our Economic Future. John Wiley & Sons. ISBN 9780470622414.
  2. ^ Gertz, Michael (2013). Integrity and Internal Control in Information Systems V: IFIP TC11 / WG11.5 Fifth Working Conference on Integrity and Internal Control in Information Systems (IICIS) November 11–12, 2002, Bonn, Germany. Dordrecht: Springer. pp. 188. ISBN 9781475755350.
  3. ^ Vallabhaneni, S. Rao (2015-01-20). Wiley CIAexcel Exam Review 2015 Focus Notes, Part 3: Internal Audit Knowledge Elements. Hoboken, NJ: John Wiley & Sons. p. 431. ISBN 9781119095194.


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Notes

This article is a direct transclusion of the Wikipedia article and therefore may not meet the same editing standards as LIMSwiki.

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