Administration and Communication II Practice Test

A robust data governance framework establishes clear ownership, standards, and processes for data—how it’s defined, validated, stored, secured, and who may use it. When these elements are in place, data becomes reliable, traceable, and compliant, which in turn supports well-informed decision-making. You get consistent definitions, data quality checks, and metadata that explain where data comes from and how it’s transformed, all of which build trust in the data you rely on for decisions. Compliance is built into the framework through policies, audits, and controls that align with laws and regulations, making it easier to demonstrate adherence.

Faster data deletion isn’t the primary outcome—retention and deletion policies may exist, but speed is not the core value of governance. Reduced data accuracy runs counter to governance goals, which aim to improve accuracy through standards and quality controls. Increased data silos contradict the purpose of governance, which aims to enable sharing and standardization across the organization. The strongest result is reliable data, compliant operations, and the ability to make informed decisions.