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!
2015 Visual Analytics Interactive RoadshowSAS(r) experts are coming to a city near you in a series of live, interactive workshops focused on SAS Visual Analytics, including how to prepare your data for VA, the integration of VA with Office Analytics and a Visual Statistics demo.
January 22: King of Prussia, PA
February 24: Austin, TX
March 26: Redwood City, CA
April 22: NYC, NY (1st of 2 stops)
May 13: Seattle, WA
June 18: Minneapolis, MN
July 21: Rockville, MD
August 18: Chicago, IL
September 24: Irvine, CA
October 9: Cary, NC (during SAS Championship)
October 21: NYC, NY (2nd of 2 stops)
November 17: Orlando, FL
December 8: Atlanta, GA
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
The hospitality industry gathers massive amounts of customer data, and mining that data effectively can yield tremendous results in terms of improved CRM, better-targeted marketing spend, and more efficient back-end processes. Roger Ares, vice president of analytics at Hyatt Corp., discusses the ways he and his staff use big data.
Charged with keeping track of travel assets, including employees, iJET International relies on data management best-practices and advanced analytics to keep its clients in the know on current and potential world events affecting travel, Rich Murnane, Director of Enterprise Data Operations & Data Architect, told All Analytics in an interview from the 2014 SAS Global Forum Executive Conference.
Jason Dorsey, chief strategy officer for the Center for Generational Kinetics and keynote speaker at last month's SAS Global Forum 2014, describes how Gen Y professionals are enhancing the makeup of multigenerational analytics organizations.
From analytics talent development to the power of visual analytics, All Analytics found a variety of common themes circulating throughout the exhibition floor and session discussions at the 2014 SAS Global Forum and SAS Global Forum Executive Conference events held last month in Washington, DC.
Talking with All Analytics live from the 2014 SAS Global Forum Executive Conference, Eric Helmer, senior manager of campaign design and execution for T-Mobile, discussed the importance of customer data -- starting internally -- in devising the mobile operator's marketing plans.
The big-data analytics market can be a confusing place. Among the vendors vying for your dollars are traditional database management providers, Hadoop startup services, and IT giants. In this video, All Analytics editors Beth Schultz and Michael Steinhart sit down in a Google+ Hangout on Air with Doug Henschen, executive editor of InformationWeek. Henschen discusses use cases for big-data analytics, purchase considerations, and his recent roundup of the top 16 big-data analytics platforms.
At the National Retail Federation BIG Show last month, All Analytics executive editor Michael Steinhart noted a host of solutions for tracking and analyzing customer activity in retail stores. From Bluetooth beacons to RFID tags to NFC connections to video analytics, retailers must find the right combination of tools to help optimize the shopper experience, streamline operations, and boost revenues.
The days when historical shipment trends and gut feelings were enough to forecast retail demand accurately are long over. SAS chief industry consultant Charles Chase outlines the benefits of pulling real-time sales information from point-of-sale and product scanner systems, then flowing that data into dynamic forecasting tools from SAS.
With today's advanced visual analytics tools, you can stream data into memory for real-time processing, provide users the ability to explore and manipulate the data, and bring your data to life for the business.
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.