What can be an outcome of applying summarization functions to a quantity column?

Applying summarization functions to a quantity column can significantly enhance the clarity of data presentment. When these functions are utilized, they can aggregate the data by various means, such as totals or averages, thus transforming a large amount of raw data into a more digestible format. One common outcome is the calculation of a running sum, which compiles cumulative totals over a specified time period. This running sum provides a clearer view of trends and performance over time, enabling better decision-making and analysis.

Using summarization functions effectively highlights key insights and patterns that might be obscured in a detailed dataset, thereby aiding stakeholders in understanding overall progress or performance toward goals. This capability is especially important in data-driven environments where quick interpretation and analysis of quantities are necessary for operational efficiency and strategic planning.