Data analysis is hot: every day we read about people doing complex and illuminating things with their data. It’s an exciting, dynamic time to be a professional analyst, and even people with backgrounds in statistics, engineering, or computer science have to work hard keep up with the trends in data.
But how does someone without a background in data learn to do good analysis? Everyone needs strong data skills nowadays because business is data analysis.
In my consulting work as a data analyst, I’m accustomed to being viewed by clients with a mixture of appreciation and apprehension: appreciation because they love learning about what’s inside their data, and apprehension because, well, shouldn’t they know how to do this work themselves? The answer is “yes.” As useful as hired guns like me can be, there’s no substitute for your own thinking about your data. Over the long haul, it’s not a good idea to outsource your brain. But how do you learn to analyze data?
Most books about learning data analysis aren’t much help. If a book has “data analysis” in the title, it’s usually for one of these two audiences: people who need a reference for the data analysis functions of Microsoft Excel, and people with a strong mathematical background. It’s hard to learn data analysis from these books. The Excel-oriented books are about using the software, not about understanding deep analytic principles. And the highly mathematical books presume too much prior knowledge among people who want an introduction to analysis.
The world needs an interactive, learner-oriented book that will allow intelligent data novices to grasp the tools for using data to make better decisions. And not just software tools, the big conceptual tools that underlie the best analysis and make for sharp thinkers. Head First Data Analysis, which ships in just a few weeks, was written in response to this need.
I hope that reading Head First Data Analysis is as exciting for you as writing it was for me. I can’t wait to hear what you think about it.