Data governance refers to the policies, processes, and controls an organization implements to ensure data integrity, security, and compliance. When an organization has a weak data governance culture, the most compromised attribute of data is "veracity," which refers to the accuracy, reliability, and trustworthiness of data.
Why Option D (Veracity) is Correct:
Weak data governance leads to poor data quality, inconsistencies, and errors, reducing data veracity (trustworthiness and accuracy).
Without strong governance, data may be incomplete, outdated, or manipulated, leading to flawed decision-making.
Data veracity is critical for risk management, internal audit, and regulatory compliance, as unreliable data can lead to financial misstatements and operational risks.
Why Other Options Are Incorrect:
Option A (Variety):
Variety refers to different types and sources of data (structured, unstructured, semi-structured).
A weak data governance culture does not necessarily affect the diversity of data sources.
Option B (Velocity):
Velocity refers to the speed at which data is generated, processed, and analyzed.
Weak governance impacts data quality more than processing speed.
Option C (Volume):
Volume refers to the quantity of data being processed and stored.
Weak data governance might lead to data duplication or loss but does not directly impact data volume.
IIA GTAG – "Auditing Data Governance": Emphasizes the importance of data veracity in decision-making.
COSO Internal Control Framework: Highlights the role of data integrity in financial and operational controls.
IIA’s Global Technology Audit Guide on Data Analytics: Discusses the risks of poor data governance affecting veracity.
IIA References:
Contribute your Thoughts:
Chosen Answer:
This is a voting comment (?). You can switch to a simple comment. It is better to Upvote an existing comment if you don't have anything to add.
Submit