In terms of SQL, Skewness is an asymmetry in the distribution of the data values or how the value is distributed accross.
Consider a table employees where you have millions of employee records and a column in that table which have either a value as 0 or 1 (F or T). Now consider out of one million records, the 1 value is applicable for only 2000 employees and the rest are having value as 0. This asymmetry or inproportionate data tells us that the column contains highly skewed data.
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There isn't a specific chart for skewed data, but you could use a number of different charts to show that data is skewed. An Area chart could be used for example, or a column chart could also work. It would depend in the nature of the data.
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There is no meaningful average wen data are categorical (qualitative). Also, the arithmetic mean is not a good measure of central tendency when the data distribution is skewed.
the data value that is much higher or lower than the other data given is called an outlier
If the skewness is different, then the data sets are different.Incidentally, there is one [largely obsolete] definition of skewness which is in terms of the mean and median. Under that definition, it would be impossible for two data sets to have equal means and equal medians but opposite skewness.