One option that Excel has, and that I imagine most graphing software has, is to convert one of the scales from the regular linear scale to a logarithmic one. In a logarithmic scale, the equally-spaced intervals represent powers of 10.
In the oil industry, we use log scale charts quite a lot, and they often make the data more sensical. Today I made the following scatter plot, which shows the oil to gas ratio for some wells in Oklahoma. The x axis represents how long the well has been running, so the idea is to see how these ratios might change over time, and how they vary from well to well. It came out like this (get a bigger image by clicking):
This is obviously not acceptable as a graph. The couple of really high values near the top edge make all of the more normal values clump together at the very bottom. And no matter how much I limit the range of the y axis, I get basically the same effect. Here I've limited it to 2000, which cuts off some data points:
It's better, but it's still not great. Then I tried a log scale:
And voila. Suddenly this data makes sense.
Log scales are a bit tricky for people to read, so it does help to add the minor gridlines.
The spacing of the minor gridlines helps remind you how the scale works, and you can also use them as a guide. The line immediately above 1000 is 2000, then the next one is 3000, etc., and they are spaced accordingly.
I love these types of data representation issues and when I make a display that is more intelligible than it might have been, it makes me really happy and proud.