This is unfortunate when you consider the promised benefits. Data is visually represented to summarize information and present it quickly and honestly.

Numbers are a treasure chest of information, useless, without the proper key. 1, 3, 6, 10, 15, 21, ?... What's next?

If you're no good with numbers, don't be ashamed, to most people, mathematics is a 4-letter word. Many have difficulty with puzzles, and they'll go to great lengths to avoid them.

Spotting a trend in a series of sales figures is even more demanding than the numbers above. So why do we acknowledge we're poor at the first type of puzzle, and think we're experts in the second?

Graphics can help. If you use a line graph to represent the 6 numbers, you'll practically 'see' 28 without thinking. Pie charts, stacked bar charts or other representations won't work as well.

Numbers, by themselves, mean nothing. If my sales last week totaled $10,000, you don't know whether to congratulate me or start bankruptcy proceedings. Numbers are representations of the real world, devoid of information until they're put into context.

What are the attributes of good graphics? They have no ego. The viewer's attention is drawn to the meaning of the data and not the beauty of the representation.

Graphics should be appropriate to the data. Don't use a 'closed' graphic (a pie chart) to represent time series data (sales by month.) Never imply a relationship between the data (a line graph) to represent non-related data (sales by region.)

A graphic should never mis-represent the data. In plainer words, it should not lie. Stated yet another way, a 10% increase should LOOK like a 10% increase. (Interesting assignment ... take a ruler and carefully examine graphs in your favorite news magazine ... what do all those little 'lies' imply about the media?)

We use graphics to represent data visually. If the visual representation you choose distorts the data in any way, throw it out and start over. Unless of course your desire is to deceive, because that's what the graph will be doing.

How tall is the stack of 'data' you receive each morning? What information are you trying to extract? What's important? And what's just noise? Is there a graphic to help you understand the data better? Have you sat with someone who knows graphics, to find such a representation? When you find it, you'll only need glimpse at it, to know what information your data contains.