How can Power BI users verify data integrity?

Power BI users can verify data integrity primarily by applying appropriate aggregation and validation methods. This approach focuses on ensuring that the data used in reports accurately represents the underlying data sources. Aggregation methods help summarize detailed data into a comprehensible format without losing essential insights, while validation techniques can include checking for data accuracy, consistency, and completeness. Data integrity is crucial in decision-making processes, and thorough validation methods, such as cross-referencing against known values or conducting data profiling, help to establish confidence in the data's reliability.

Generating random visualizations does not contribute to verifying data integrity, as it does not involve checking whether the data accurately reflects what it is supposed to. Reducing the size of datasets might lead to faster processing or easier sharing of reports, but it does not inherently verify the accuracy and reliability of the data contained within. Sharing reports with others allows for feedback and collaborative analysis but does not authenticate the accuracy of the data being reported. Thus, without validation methods in place, sharing could potentially propagate inaccuracies rather than ensure integrity.