When you're learning data science, you usually practice with nice, clean, pre-packaged data sets and tidy case studies that lead you step-by-step from data collection to cool insights.
But when real life hits, many data scientists have to work with missing or sketchy information extracted from (multiple) sources in the organization. Data science that works is a messy, trial-and-error process of creating and testing hypotheses, gathering evidence, and drawing conclusions.
Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist, by distinguished CSC engineer Jerry Overton, outlines practices for making good decisions in the complicated real world. These skills are far more useful for practicing data scientists than, say, mastering the details of a machine-learning algorithm.
It's an incredibly practical ebook. And it's free.
Download the free ebook → http://www.oreilly.com/data/free/going-pro-in-data-science.csp?imm_...
Chief Data Scientist, O'Reilly Media
P.S. Jerry Overton is also presenting a half-day tutorial on the topic at Strata + Hadoop World in NY in September, providing in-depth education in data science, big data architecture, and analytics for business. As an O'Reilly customer, get 30% off Early Price with code DATA30 by registering by August 12.