Every day we hear about the adventures of people who love data and know what to do with it. We again offer a random selection of data scientists -- and again we find a wide variety of expertise and experiences shaping the men and women of this new profession, data science.
Start the slideshow by clicking on the image below. And once you're done, feel free to drop a note on the message board regarding data scientists you know (or know about, at least), and take a look back at our first collection.
Current position: Senior research scientist, analytics, LinkedIn
Bio: Built the LinkedIn product analytics team from two to 10 data scientists. Spearheaded many of LinkedIn's key products: the Talent Match system that matches jobs to candidates, the first machine learning model for People You May Know, and the first version of Groups You May Like. She holds a PhD in computer science from Carnegie Mellon University.
Quotable quote: "By definition all scientists are data scientists. In my opinion, they are half hacker, half analyst, they use data to build products and find insights. It's Columbus meet Columbo -- starry eyed explorers and skeptical detectives."
I like the quotes about data not just being terabytes and the other quote that it's storytelling. I have often seen this in a couple of work places where there was plenty of data, but not enough talent to make sense of it.
I agree, Jen. I know University of Illinois received a record number of applicants for its undergrad Engineering School, a top-rated program, this year. I would suspect other schools, and other tech disciplines, would report the same.
Hi Gil, interesting mix of people here (and, as a female, I'm pleased to see several women mixed up in this bunch of data scientists). I particularly like Monica Rogati's quote, "By definition all scientists are data scientists. In my opinion, they are half hacker, half analyst, they use data to build products and find insights. It's Columbus meet Columbo -- starry eyed explorers and skeptical detectives." That last piece brings to mind the "Holmes vs. Columbus" Point/Counterpoint debate we ran not too long ago!
LEADERS FROM THE BUSINESS AND IT COMMUNITIES DUEL OVER CRITICAL TECHNOLOGY ISSUES
The Current Discussion
Visual Analytics: Who Carries the Onus? The Issue: Data visualization is an up-and-coming technology for businesses that want to deliver analytical results in a visual way, enabling analysts the ability to spot patterns more easily and business users to absorb the insight at a glance and better understand what questions to ask of the data. But does it make more sense to train everybody to handle the visualization mandate or bring on visualization expertise? Our experts are divided on the question. The Speakers: Hyoun Park, Principal Analyst, Nucleus Research; Jonathan Schwabish, US Economist & Data Visualizer
Dynamic data visualizations let analysts and business users interact with the data, changing variables or drilling down into data points, and see results in a flash. Advance your use of data visualization with tools that support features like auto-charting, explanatory pop-ups, and mobile sharing.
No doubt your enterprise is amassing loads of data for fact-based decision-making. Hand in hand with all that data comes big computational requirements. Can traditional IT infrastructure handle the increasing number and complexity of your analytical work? Probably not, which is why you need a backend rethink. Big data calls for a high-performance analytics infrastructure, as Fern Halper, a partner at the IT consulting and research firm, Hurwitz & Associates, discusses here.
Redbox's bright-red DVD kiosks are all but ubiquitous these days, located in more than 28,000 spots across the country. Jayson Tipp, Redbox VP of Analytics and CRM, provides an insider's look at how the company has accomplished its phenomenal nine-year growth.
InterContinental Hotels Group (IHG), a seven-brand global hotelier, has woven analytics into the fabric of its operations. David Schmitt, director of performance strategy and planning, shares IHG's analytics story and his lessons learned.
Elizabeth Barth-Thacker, a BI and informatics technology manager at Humana, tells us how her team is creating data transparency and building engagement with the business – with the help of an internal collaboration portal called Humanalytics.
Whether working in major league sports, financial services, or healthcare, analytics, and data, professionals are checking out how visual analytics and high-performance technologies can help them optimize their environments, shrink their cycle times, and improve decision making, as attendees at the recent SAS Executive Briefing in New York share with us.
Jim Davis, SVP and CMO at SAS, talks with us at a recent SAS Executive Briefing about how high-performance analytics and visual analytics take away the concerns over big-data and let companies get down to business with their data.