WhatsTheBigData

From Simon Rogers, “What is a Data Scientist?”:

“Someone who can bridge the raw data and the analysis – and make it accessible. It’s a democratising role; by bringing the data to the people, you make the world just a little bit better.”–Simon Rogers

“A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.”–DJ Patil

“A data scientist is someone who blends, math, algorithms, and an understanding of human behavior with the ability to hack systems together to get answers to interesting human questions from data.”–Hilary Mason

“A data scientist is a rare hybrid, a computer scientist with the programming abilities to build software to scrape, combine, and manage data from a variety of sources and a statistican who knows how to derive insights from the information within. S/he combines the skills to create new protoypes with the creativity and thoroughness to ask and answer the deepest questions about the data and what secrets it holds”–Jake Porway

“The four qualities of a great data scientist are creativity, tenacity, curiosity, and deep technical skills. They use skills in data gathering and data munging, visualization, machine learning, and computer programming to make data driven decisions and data driven products. They prefer to let the data do the talking.”–Jeremy Howard

“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.”–Monica Rogati

Shawn Hessinger at AllAnalytics.com summarizes yesterday’s e-chat with Gartner’s Doug Laney on what data scientists do and who they are. Gartner’s definition of a data scientist:

Responsible for mining, modeling, interpreting, blending, and extracting information from large datasets and then presenting something of use to non-data experts. These experts combine expertise in mathematics-based semantics in computer science with knowledge of the physics of digital systems.

And Laney thinks that a “A good data scientist could probably be a good data scientist in any industry and with almost any problem.”

Chuck Hollis calls Data Scientists “rock stars” and argues that they are “a fundamentally different profession with a different profile than the BI analysts that came before [them].  They’re more likely to have advanced degrees, frequently have a background in the sciences (vs. business) and they interact with data in more ways — and using different tools.”

Over at Vator they call them “rocket scientists” and “data junkies.” And an article in the November/December issue of the IEEE Intelligent Systems explores a “what if” scenario in which data scientists are criminals. No quotation marks.

Asking good questions as the key to unleashing the potential of big data got significant blog time this past week. Continue reading →