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Big Data

I’ve been thinking a lot lately about the skill set engineers graduating in the next few years will need to prepare them for a vibrant and productive career.  I can think of very few skills that rival big data analytics in importance for the next generation of engineers.  We continue to collect data on a vast scale every day.  We need to look no further than data.gov, the repository of an astounding array of data from a huge swath of government agencies on subjects ranging from the crucial to the mundane.  Data and analytics are everywhere, in every aspect of our lives; to wit:

  • commerce: the NYT ran a fascinating article on Target and its data collection and analytics efforts on its customers
  • health: from the Nike+ system (which I’ve been using since 2007) to the Zeo sleep system, personal data collection systems are popular, growing in their diversity, and increasingly powerful
  • sport:  perhaps my favorite example, the Manchester City Football Club (England) has started an MCFC Analytics initiative, in which they release player performance data to the community, and the community is encouraged to analyze, graph, and otherwise break down the data “however you see fit”

Big data is here to stay, and everyone–engineer or not–needs basic literacy about how to access, analyze, interpret, and otherwise engage with data.  So it is incumbent upon the faculty in higher education to give students opportunities, experiences, and training around this critical skill set.

Big data hits upon several of the key student learning outcomes that educators have wrestled with for many years:

  • an ability to pose research questions and gather sufficient resources/evidence to answer those questions
  • a general comfort with uncertainty, lack of complete information, poor signal-to-noise ratio, etc.
  • the ability to conduct data analysis, especially on large data sets, using modern computer tools
  • the ability to visualize data, and use graphics to tell a persuasive story about what the data means

These basic skills are part of the new literacy for all engaged citizens–not just scientists and engineers.  And developing curricula around big data opens up some enticing new possibilities on student motivation and engagement:  students can choose to ask and answer research questions about which they care, in topical areas that are meaningful to them.  A student interested in environmental issues could analyze public data sets about pollution, air quality, or water quality.  A student passionate about economics could look at unemployment rates, pay scales, or international trade.  A student interested in energy could examine subsidies for green energy companies, consumption locally and worldwide, or performance data for various alternative energy technologies.

There’s much more to say here.  But preliminarily the point is that when it comes to education and the future of an educated citizenry, basic literacy about how to understand data is more important than ever before.

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