SAS customers are both bright and generous. Recently, I met several who gathered to discuss SAS Enterprise Miner and SAS Model Manager predictive analytics and data mining software.

Hiring the best
I loved listening to their discussion on what they look for and how they find the people who will help them build an analytics culture in their own companies.

One described liking to hire people with an entrepreneurial mindset—the ones who will be willing to promote their ideas to fruition.

Another looks for those who have a forensic mindset—the ones who don’t stop investigating when they get an answer but work to understand why that’s the answer.

One hiring manager describes a problem and gives the candidate a day to work with the data to create a model addressing the issue. Then, rather than simply judging whether the model they created is good or bad, it’s most important to see which inferences and decisions the candidate makes along the way.

Another gives a math test, asking the candidate to multiply two matrixes, solve an algebra story problem, do a derivative as well as talking through their experiences applying analytics to business problems.

Building skills
A key skill is being able to communicate analytic findings to nontechnical people. One person invites a new analyst on the team to present an analytics result to the company’s board of directors. It helps these employees learn how to read expressions and body language so they know when they have clearly communicated the importance of analytics.

More popular than ever, conferences including Analytics 2012 this June in Germany and then also in the U.S. October 8-9 showcase real-world case studies and the latest trends and methodologies, allowing analytics practitioners share ideas and stay at the forefront in their field.

In this age of rising college education costs, it was exciting to hear which books our customers recommend that data miners read to stay sharp and up-to-date. Some books help readers understand the business side of predictive analytics, some focus on the mathematics of analytics, and others help analysts improve how they communicate analytic results to business executives. Read a few pages at each of the links below and you may find one you’d like.

Staying current
• Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be was a popular choice for understanding the key role of analytics in business management today. It’s about decision makers relying on analytics to deliver staggeringly accurate results.

• The Black Swan, a New York Times Bestseller, was recommended to help analysts understand the relevance of events that are deemed improbable yet cause massive consequences.

• The Cartoon Guide to Statistics puts you on the road to statistical literacy. It covers all the central ideas of modern statistics simply with funny illustrations, providing an easy and visual way to learn statistics.

• The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition is written by three giants of the data mining community. Very technical, but very complete. Topics covered in this book not usually covered in others.

• Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) provides an excellent balance between highly technical and introductory books on the topic.

• Introduction to System Dynamics was recommended as an aid for problem solving--helping leaders determine the effect of an organization’s systems on other parts of the organization.

• Assuming only a limited knowledge of higher-level mathematics, Using Multivariate Statistics provides an introduction to today's statistics and multivariate techniques.

• Competing on Analytics: The New Science of Winning shows how high-performing enterprises are now building their competitive strategies around data-driven insights.

Maybe you’re advising friends or family or you just appreciate staying current on the latest in data mining methodology.  Which books do you recommend?

What do you look for in new hires as you help build your company’s analytics culture?