With a deluge of data available in raw digital form, and presentation software becoming more sophisticated, data visualization offers powerful ways for people to make sense of large amounts of data in a way that plain numbers don't quite manage. Potentially it is also a way to bypass, or counterbalance, the spin of politicians and lobbyists by making the sources of their claims available for public scrutiny.
Of course, the practice of data visualization, or infographics, is not new - it's probably as old as writing, from maps and genealogical trees to fullblown taxonomies of the known world. (For some beautiful examples, see these 'Victorian Infographics'.)
The difference these days is that online infographics can be a) interactive, allowing users to explore data themselves, and b) dynamic, meaning they can be based on live data. One of the most ambitious examples of the former is 'Gapminder', while many of the endless Twitter visualizations are examples of the latter.
The downside to all this is not just the great number of visualizations of trivial data (which remains just that, even when visualized), but also a whole range of possible misrepresentations. The use of logarithmic scales in financial projections may be the most notorious example, but there's a whole bag of other statistical fallacies. These are not new either (as the saying goes, there are "lies, damned lies, and statistics"), though eye candy will do a lot in obscuring them.
Which calls for statistical literacy in this emerging field, where journalism, design and programming meet, and where awesome data stories are yet to be told.
Update: Statistical literacy is at #1 of Wired's list of '7 Essential Skills' for a 21st century education.