Big Data

Big data refers to a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. That is, beyond current comfort levels. Big data made a splash in 2012, but it is now recognized that “big” is relative, depending on context, amount of data and complexity of the problem. Gartner glibly identified the “3 Vs” of big data–volume, velocity and variety– which were recently expanded by Inderpal Bhandar to include another 3 Vs: veracity, validity and volatility. Statisticians, and data modellers in general, might also want to include 3 Us: unknowns, uncertainty, and unfamiliarity. Below is a compilation of links related to big data.

• UW-Madison’s relationship with Big Data
• Big Data 2013 (NY Times, 21 Jun 2013)
• Big Data: A Perspective from the BLS (Amstat News, 1 Jan 2013)
• Big Data: The Management Revolution (HBR, Oct 2012)
• White House Announces Big Data R&D Initiative (29 Mar 2012):
  • Taking a Scientific Approach to Science and Engineering Education (Carl Weiman, White House Office of Science and Technology Policy, 20 Mar 2012)
  • WebCast
  • White House Big Data Fact Sheet
  • White House Press Release
  • Big Data is a Big Deal (White House Blog)
    
  • NSF Leads Federal Efforts In Big Data (NSF)
  • Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA) (joint NSF/NIH RFA: due 13 Jun/11 Jul 2012)
    • NSF 12-499 Solicitation
    • NIH NOT-GM-12-109 Solicitation (refers back to NSF page)
    • NSF FAQ on BIGDATA
  • White House to Announce Big Data R&D Initiative (CCC Blog): White Papers with Challenges & Opportunities
  • White House Shares $200 Million Big Data Plan (InfoWeek)
  • Feds launch big data initiative to advance science (CNET)
  • Big Data, Meet Big Government (Portfolio.com)
  • New U.S. Research Will Aim at Flood of Digital Data (NY Times)
  • Mining of Massive Datasets (Stanford U)
  • Evolution of Translational Omics: Lessons Learned and the Path Forward (IOM)
• AMP Lab, UC-Berkeley
• 1000 Genomes Project
• Information Week’s Big Data Section
• Wolfram Alpha
• Chiliad
  
• Careers in and News on Big Data
  • Training Students to Extract Value from Big Data: Summary of a Workshop (2014 NAP)
  • Managing Large Data Sets (Amstat News, Jul 2014)
  • Statistical Scientists Advance Federal Research Initiatives (Amstat News, Jul 2014)
  • The Risks of Big Data for Companies (NY Times, Oct 2013)
  • Think You’re Too Small for Big Data? (Kellogg Magazine, Jul 2013)
  • Big Data TechCon
  • Most Creative People 2013: 1. Nate Silver (Fast Company, May 2013)
  • Data Science: The Numbers of Our Lives (NY Times, Apr 2013)
  • Luring Young Web Warriors Is Priority. It’s Also a Game (NY Times, Mar 2013)
  • Big Data Is Opening Doors, but Maybe Too Many (NY Times, Mar 2013)
  • How to Fill Big Data Talent Gaps Fast (Information Week, Jan 2013)
  • Data Scientist: The Sexiest Job of the 21st Century (HBR, Oct 2012)
  • Growing your own Data Scientists (Dan Woods, CITO Research)
  • What is a Data Scientist? (interview with Michael Rappa, NCSU, Forbes, 5 March 2012)
  • Why Statistics? (M Davidian, TA Louis, Science, 6 April 2012: 12)
  • Agencies Rally to Tackle Big Data (J Mervis, Science 6 April 2012: 22)
  • Data Deluge Selected as Theme for Mathematics Awareness Month (Amstat News, 1 Apr 2012)
  • Twitter Data Scientist Takes on McDonald’s Entire Menu, Survives (Technology Review, 22 Mar 2012)
  • The Age of Big Data (NY Times, 12 Feb 2012)
  • Big data: The next frontier for innovation, competition, and productivity (McKinsey Report, 2011)
  • Big data analytics now worthy of a masters degree, IBM says
  • Big data, but are we ready? , by Trelles, Prins, Snir and Jansen, (Nature Reviews Genetics 12: 224 2011)
  • Computational solutions to large-scale data management and analysis, by Schadt, Linderman, Sorenson, Lee & Nolan (Nature Reviews Genetics 11: 647–657, 2010)
    
  • More Statistics Career Information