Polly Mitchell-Guthrie leads the Advanced Analytics Customer Liaison Group in R&D, connecting with customers to improve SAS products. At SAS for 14 years, Polly has held a variety of roles in finance and alliances, and the Global Academic Program. She has a BA and MBA from the University of North Carolina at Chapel Hill.
I recently met Mrs. Claus at the INFORMS Annual Meeting, where we got to talking about the social network analysis session she’d just attended. It turns out Mrs. Claus and I are both fans of a book by Alex Pentland, Social Physics: How Social Networks Can Make Us Smarter. Apparently
In honor of today’s #GivingTuesday, which "harnesses the potential of social media and the generosity of people around the world to bring about real change in their communities,” I’ve been thinking about what constitutes “real change” and the role analytics can play on the many social issues our planet faces.
Who says machine learning can't be fun? A crew of us from SAS went to San Francisco for the recent KDD conference, which bills itself as "a premier interdisciplinary conference, [which]brings together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data." We brought
Asking about the benefits of artificial intelligence and machine learning reminds me a little of the transition to suitcases with wheels. Do you remember lugging around those old suitcases? If not, good for you - this original advertisement from US Luggage will take you back! Thank Bernard Sadow for persistence with his
Analytics, statistics, operations research, data science and machine learning - with which term do you prefer associate? Are you from the House of Capulet or Montague, or do you even care? Shakespeare's Juliet derides excess identification with names in the famous play, Romeo and Juliet. "What's in a name? That which we call
My view of the world is shaped by where I stand, but from this spot the future of analytics for 2016 looks pretty exciting! Analytics has never been more needed or interesting. Machine learning established in the enterprise Machine learning dates back to at least 1950 but until recently has
Can pattern recognition software tell us if it is a Hermit Thrush or a Swainson's Thrush we've seen? A few of us have been debating an identification question at work, because we agreed to help Fulbright Scholar and Duke University PhD student Natalia Ocampo-Peñuela with research she is doing related to bird collisions with windows. A sad
Ok, so the title is a little provocative, but some people are dubious that data science training is even possible, because they believe data science entails skills one can learn only on the job and not in a classroom. I am not in that camp, although I do believe that data
How do we hire data scientists at SAS, since we are not unique in our search for a rare talent type that continues to be in high demand? This post is the last in a series on finding data scientists, based on best practices at SAS and illustrated with some
Because finding analytical talent continues to be a challenge for most, here I offer tips 5, 6, and 7 of my ten tips for finding data scientists, based on best practices at SAS and illustrated with some of our own “unicorns.” You can read my first blog post for why they
Finding people with the range of skills classified as data science can be a challenge, which is why some call them unicorns (do they really exist?), so I recently posted ten tips on finding unicorns. In my first post I elaborated on tips 1 and 2 (1. hire from an
As this article on the mythical data scientist describes, many people call this special kind of analytical talent "unicorns," because the breed can be so hard to find. In order to close the analytical talent gap that McKinsey Global Institute and others have predicted, and many of you experience today, SAS launched
At the KDD conference this week I heard a great invited presentation called How to Create a $1 billion Model in 20 days: Predictive Modeling in the Real World – A Sprint Case Study. It was presented by Tracey de Poalo from Sprint and former Kaggle President and well known
Looking forward, ten of my SAS colleagues and I are heading to New York City this weekend for KDD 2014: Data Science for the Social Good, which runs August 24-27. This event’s full name is the 20th Association for Computing Machinery Special Interest Group on Knowledge Discovery and Data Mining,
I'm a big believer in both/and thinking, so I'll stand squarely in the middle and say that the most important skills for competitive advantage in analytics include a combination of top-notch modeling abilities along with business acumen, critical thinking, and curiosity. I was intrigued by a blog post on this
How many analytical projects have foundered due to lack of problem definition and other soft skills? As my SAS colleague Sascha Schubert writes, people and process matter, in addition to great technology. Great technology is a great first step, but having the right people following the right process is critically important.
Andy Pulkstenis of State Farm thinks it is, stating that this red-headed stepchild among modeling technques is where predictive modeling was ten years ago. He opened his talk, "Do You Know or Do You Think You Know? Creating a Testing Culture at State Farm," at the A2012 conference in Las Vegas with
At Predictive Analytics World San Francisco this week I attended back to back sessions on econometrics, a word that doesn’t surface as often as I think it should. Bestselling books like Freakonomics: A Rogue Economist Explores the Hidden Side of Everything or Predictably Irrational: The Hidden Forces That Shape Our
“Wise Enterprise: Best Practices for Managing Predictive Analytics” was the title, and the assignment to the panel at the recent Predictive Analytics World conference in New York was to share “poignant moments of failure.” Wayne Thompson from SAS began, going back ten years to describe a network intrusion project. He
