Only two columns are numeric, and they behave very differently: `Sr No` is a row ID, while `Amount in USD` is a heavily right-skewed measure. The rendered table from the profiling query shows the full figures. **Amount in USD** (stored as text; I stripped commas and cast) - **Coverage:** 2,065 of 3,044 rows parse to a number. The other 979 are null or non-numeric, so every statistic below describes only the 2,065 parsed deals. - **Range:** the smallest deal is $16,000 and the largest is $3.9 billion. - **Centre:** the mean is about $18.4M, but the median is only $1.7M. The mean is roughly 11 times the median, which points to a long right tail. - **Spread:** - The middle half of deals runs from $470K (25th percentile) to $8M (75th percentile), an interquartile range of about $7.5M. - The 95th percentile is $60M. - The population standard deviation is about $121M, roughly 6.6 times the mean. - **Interpretation:** most deals are small, a handful of very large ones pull the average up, and the mean is misleading here. Use the median and percentiles for benchmarks such as typical ticket size. The sample standard deviation function failed with an out-of-range error on these extreme values, so I report the population standard deviation, which ran without error. **Sr No** (row identifier, not a measure) - It runs from 1 to 3,044 with no gaps. The mean and median are both 1,522.5, and the standard deviation is about 879. - These figures just describe an evenly spaced sequence and carry no analytical meaning.