Business Intelligence Exam Practice 2025 – Complete Prep Guide

Data integrity in Business Intelligence refers to maintaining accuracy and consistency of data throughout its lifecycle. It is crucial for ensuring that the information used for decision-making is reliable and trustworthy. When data integrity is upheld, it means that the data reflects the true values and information it is intended to represent, which is vital for effective analysis and reporting.

Accurate data supports better decision-making, avoids discrepancies, and helps build confidence in the business intelligence processes. This includes measures to prevent unauthorized alterations to the data, regular audits to validate data accuracy, and employing processes to detect and correct errors as they occur.

While speed of processing, the ability to scale storage solutions, and collaborative sharing of data among departments are important aspects of a business intelligence system, they do not directly define data integrity. Instead, they serve complementary roles that can enhance the overall effectiveness of business intelligence efforts. Therefore, maintaining accuracy and consistency is the cornerstone of data integrity in BI.