In which context is a histogram employed during data preparation?

A histogram is particularly useful in examining measure and date fields for outliers because it visually represents the distribution of numerical data points. When data is plotted in a histogram, specific bins (ranges) indicate how many observations fall within each range. This can make it easier to identify data points that deviate significantly from the rest of the dataset, which are classified as outliers. Outliers are essential to recognize because they can skew the results of analysis if not addressed, potentially leading to inaccurate interpretations and conclusions.

The other options do not align as closely with the primary purpose of histograms. Visualizing categorical data distributions is typically done with bar charts, where distinct categories are compared rather than a continuous range of values. Creating trend lines for time-series data is better suited for line charts or scatter plots that can depict change over time rather than frequency distributions. While a histogram may provide insight into the general distribution from which mean and median values can be derived, its primary role is not to calculate those values but rather to visualize the underlying data structure.