Friday, November 25, 2011

Basic Lesson on Data Analysis

A friend asked me how to approach data analysis and how to decide on the data presentation.

From my experiences and reading, Dan Roam in his book, The Back of the Napkin had explained the process very well. Below is the excerpt from his book with my two-cents' worth thrown in.

Data analysis is both an art and a science. It is increasingly important due to the advent of Internet. Today, we are flooded with information. The sad thing though is that, we are inundated with details at the expense of the big picture. While in the past data was power, today making sense of data is more powerful. In essence, we need to be able to separate the wheat from the chaff.

How to Look Better - 4 Rules to Live By

1. Collect everything we can look at, the more the merrier (at least at first)

2. Have a place where we can lay down everything and ready look at it, side by side

3. Always define a basic coordinate system to give us clear orientation and position

4. Find ways to cut ruthlessly from everything our eyes bring in - we need to practise "visual triage".

Remember: When data is packed in individual tiles and records, it is impossible to look at the big picture - but getting everything out in the open makes otherwise invisible connections visible.

General Rules of the Thumb

1. It's the data that matters, let it show.

Many people find numbers boring, so we jazz up our charts with visual bells and whistles hoping to make pictures more interesting

That's only the style. In my opinion, substance is the most important ingredient. Let us face it, insightful data is exciting! If what we show resonates with our audience (either it shows exactly what they hope for or it scares the daylights out of them), they won't fall asleep.

2. Always show the fewest possible pictures to make a point.

Less is more. Pick the simplest model to make your point. I prefer charts to tables as the former provides hooks to catch our visual memory. In the case of tables, if we cannot remember the precise numbers, we would not have a larger context to fall back on. On the other hand, with pre-cognitive quantity charts, it enables our eyes to read immediately, compare and viscerally recall long after we have forgotten the numbers.

However if the differences among the slices are critical and yet too small to be visually detectable, one is better off with the non-pictorial table.

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