What must be done to ensure data integrity in business intelligence?

Ensuring data integrity in business intelligence is crucial for making informed decisions based on accurate and reliable information. Implementing data integrity checks is essential as it involves systematic procedures to verify and validate the accuracy, consistency, and reliability of data over its entire lifecycle. This includes processes such as data validation, data cleansing, and regular audits to detect discrepancies or errors within the data. By establishing these checks, organizations can maintain high-quality data that reflects true business conditions, supports effective analysis, and enhances decision-making processes.

Defining market share goals and increasing marketing efforts may be important aspects of business strategy, but they do not directly address the reliability or accuracy of data used for analysis in business intelligence. Limiting data sources to one might simplify data management but can also introduce bias and restrict the comprehensiveness of the insights gained, which further undermines data integrity. Thus, while all the choices provided address various aspects of business operations, only implementing data integrity checks directly focuses on assuring the trustworthiness of the data essential for effective business intelligence.