Why Women Make Great Data Scientists
Michael Walker, 2/27/15
Commentary by Janet Kamin
Michael Walker starts his blog with faint praise for women, saying that when asked whether women would make good data scientists he says, "yes", because data scientists need to challenge assumptions, to be contrarian, and women are that. He goes on to talk about some other skills that are required for a good data scientist, like good communicators and great team players. These are areas where women have traditionally excelled.
He ends by saying, "The goal is to use data science to help organizations turn data into information - information into knowledge and insights - and valuable, actionable insights into better decision-making and game changing strategies. Women have the potential to be among the best data scientists and I predict many will become effective future leaders in the profession. "
Study Uses Big Data To Track Link Between Social Activity And Urban Movement
Dianne Depra, 2/28/15
Commentary by Janet Kamin
Walking around in the city, with all the hustle and bustle, I sometimes wonder, "where is everybody going?". This week Dianne Depra reported on a study done at MIT, and published in the journal Interface, that answers just that. Jameson Toole, one of the authors for the study, explained that they were able to determine how much of a city's movement was social in nature by layering mobile and social data over the other. The study was conducted in three big cities in South America and Europe, and identified three classes of social movement: distant acquaintances, work colleagues and social companions. The study concluded that these three networks account for approximately 30% of all movement around cities. The article left me wondering, though, about the ratio of work related vs. social related movement in my city. I'd love to see this replicated for the major cities in the United States.
Fogs, Logs and Cogs: The Newer, Bigger Shape of Big Data in the Internet of Things (IoT)
James Kobielus, 2/26/15
Commentary by Janet Kamin
James Kobielus' most recent article on the IofT reads a little like a Dr. Seuss story, by his own admission. But he assures us that his vision of a world where everything is connected to everything else is well under way. Fogs are interconnected clouds that do the storage and most of the computation, though they are connected to local nodes.
Local nodes, including our phones and other wearable devices, do active computing while also sending information back to the fog. Logs contain all the information flowing back and forth. Finally, by cogs, Mr. Kobielus is referring to the deep learning and AI that puts all the information together to make our world run more smoothly and in a more automated way - from electrical grids, to our cars.
Quoting from mr. Kobielus, "This is more than a vision. The IoT big data fog is rapidly becoming a reality. Joshua Whitney Allen does a good job of discussing the status of fog computing efforts in industry by providing an overview of IBM’s efforts in this area. He specifically cites the partnership with Nokia to develop the world’s first mobile edge computing platform that can run applications directly within a mobile base station. The IBM and Nokia fog platform accelerates delivery of media-rich, low-latency services to smartphones by ensuring that content is transmitted from base stations rather than a remote media center. Allen also alludes to potential applications of big data fog computing to mobile gaming, augmented reality, smarter traffic and public safety."
It's Time to Invite Data Scientists to the Board Room
Beth Smith, 2/2/15
Commentary by Janet Kamin
When the President of the United States makes a video appearance at the Strata conference in San Jose, you know it's time for the data scientist to move up in the world. When asked why he was speaking to the group, Porua said: “Understanding and innovating with data has the potential to change the way we do almost anything for the better.”
And this echoes Beth Smith's experience at IBM, "Hadoop is no longer a technology only topic. CEOs are asking about Hadoop. It’s now a boardroom discussion." Her main point is that data alone is not enough to drive insights - even the most brilliant data scientist can only benefit if the team includes domain experts. The sweet spot for data science is at the intersection of data, data analytics, and the domain experts who sit in the boardroom.
The Unfriendly Skies: A Data-Driven Breakdown of What We Hate About Major Airlines
Justin Tenuto, 2/25/15
Commentary by Janet Kamin
The most fun article that caught our attention this week was Justin Tenuto's sentiment analysis of airline tweets published on Crowd Flower (which never disappoints). 20,000 tweets were collected over the course of February, and Mr. Tenuto and his team looked at what people were tweeting about various airlines. Most of the tweets were complaints, no surprise there really. The complaints were categorized into the following groups: customer service, late flight, cancelled flight, lost luggage, bad flight, booking experience, flight attendant, long lines, damaged luggage. Now here's the fun part. The predominant complaints were complaints about customer service! Data science loves irony.
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