Constructing and Evaluating Your Design Solution - Data Visualization: A Successful Design Process - page 170

Try not to weigh yourself down with too many thoughts of regret around "wish I'd
not done this" or "wish I'd managed to include that". Instead, put all reflection to
best use as a learning experience to inform your development and preparedness for
future opportunities.
Developing your capabilities
The project is over. You can take a deep breath and relax. Well, at least for an hour
until your next project is lined up!
For you the bigger picture now is to consider your ongoing development in this
discipline, learning from each experience, and building up your expertise.
The single most important message that I want to put across in this topic is the value
of practice, experience, and ongoing self-improvement. Data visualization is such a
multidimensioned and rapidly evolving craft that cannot be mastered overnight.
Earlier we looked at the framework of the "eight hats". Through assessing yourself
against this collection of capabilities, skills, and attitudes you can self-determine
where your strengths and weaknesses may be and then look to address them.
There are several strategies to help ensure your development continues.
Practice, practice, practice!
When it comes to developing your practical design skills the major piece of advice is
simple—practice, practice, and more practice. There are so many different variables
and subtle challenges involved in every project that you can't fail to learn from each
project that you undertake.
We've just reinforced that data visualization is a craft. You need to continue to
exercise your creative and analytical muscle to stay in good shape.
If time permits, try forcing yourself to stick to a practice agenda: maybe, do small
personal projects every week then a bigger project every month. You might never
launch the work in public but just testing yourself against the challenges of gathering
data, analyzing, and presenting it will help maintain your development.
An especially ideal opportunity for practice exists through the frequent data
visualization contests that are held these days, often with added incentive of prizes
for the best-judged work. These typically involve a basic design brief, a published
dataset, and a timeframe to create a compelling solution. A great value of these
contests comes from seeing all the other solutions that are submitted. This lets you
learn how others have tackled the same problem but maybe in different ways as
compared to your own approach.