Choose a subject, any subject. Andy Kirk has published a great directory of sites and services for accessing (mostly) structured data sets at his site, Visualizing Data. It’s nicely organized into these categories:
I can not wait to start exploring!
Nathan Yau provides a great summary of resources for improving your data visualization skills in this post on Flowing Data.
- Read the classics of Edward Tufte, like the Visual Display of Quantitative Information and others (including Yau’s excellent books)
- Gather data
- Do visualizations
- Share visualizations and get feedback
- Go back to your readings and start again
Yau’s post is titled Getting started with visualization after getting started with visualization – and points to iterative aspects of learning by reading, doing, sharing, doing again.
The New York Times‘ Bits Blog profiles Alastair Croll’s book Lean Anaytics at
Interesting ideas about experimentation, failure and leadership.
Experimentation, of course, involves a lot of failure, as failure is where most learning takes place. Data around the failures of others are collected and studied as part of the overall process now. Data on failure is cheaper to create, and cheaper to come by. That is another way of saying that people are more likely to make new and interesting mistakes, instead of the same old ones, which is probably a good thing.
One big result of this failure-driven world, Mr. Croll says, is that organizational leadership is changing toward a more structured learning environment. “In the past, a leader was someone who could get you to do stuff in the absence of information,” he says. “Now it’s the person who can ask the best question about what’s going on, and find an answer.”
Favorite quote from Nick Kolegraff’s Do You Need a Data Scientist? on the O’Reilly Media site:
Focus on getting accessible quality data and solid reporting. Then worry about data science. You’ll save money and efficiency.
Good data is not always big data, so let’s not over-engineer our solutions.