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CIO Scholarship Foundation

The Management Information Systems department at San Jose State University is pleased to announce a scholarship opportunity sponsored by the CIO Scholarship Foundation. The foundation represents a local non profit organization of IS executives that strives to enhance future leadership in the information systems and technology fields by supporting students studying in related fields throughout the San Francisco Bay Area.

This year we will award two one-time scholarships of $2000 each to deserving San Jose State undergraduate students majoring in Management Information Systems, Computer Science and/or Computer/Software Engineering. In addition to being declared as one of these majors, eligible candidates must be in "Good Standing," academically, with a 2.5 GPA or better. Also, candidates must be available to attend the CIO Scholarship Fundraiser event in Livermore, 12pm-8pm, October 16, as a guest of honor.

Applications are due no later than 12:00pm on Thursday, September 10, 2015.

To apply, complete the form at the following link, including an essay (500 words max) to make a succinct and compelling case for how this award would help you toward the scholarship's goal of developing the next generation of information technology leaders in the Bay Area.   

CIO Scholarship Application

Applications ALSO REQURE an email to the selection committee chair, Dr. Timothy Hill ( with the subject line "CIO Fund Scholarship Application". An up to date resume must be attached, along with all transcripts of your college-level coursework at SJSU and elsewhere.

New Elective:  Big Data BUS4 118S-02

McKinsey has estimated that we face a shortage of 1.5 million managers and analysts that have the know-how to understand and make decisions based on Big Data. In this course we will explore how different industries and the public sector are using Big Data, the Big Data life-cycle and data characteristics, operational issues relating to developing the business proposition, ethical considerations, and communicating the outcomes. We will also look at current tools in this area, with a focus on data wrangling and visualization since they are currently 80% of the effort in a Big Data project.

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