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Big data analysis is the extraction of value from the large untapped pools of data in the digital universe. The “digital universe” is defined as a measure of all the digital data created, replicated, and consumed in a single year and includes things such as images and videos on mobile phones uploaded to YouTube, digital movies we watch on high-definition TVs, banking data swiped at an ATM, security footage at airports and major events, subatomic collisions recorded by the Large Hadron Collider at CERN, transponders recording highway tolls, voice calls on digital phone lines, and texting (John Gantz and David Reinsel, The Digital Universe in 2020, IDC iView, December 2012). It is predicted that the digital universe will double every two years between now and 2020.
From health care to high tech, from education to energy providers, more and more industries are generating massive amounts of information. In the era of big data, skilled analytics professionals are needed to make sense of the information companies, governments, and educational institutions are collecting.
As businesses seek to maximize the value of vast stores of available data, employees will be needed to fill the growing demand for individuals who can learn from that data and predict and forecast consumer behavior. The Bureau of Labor Statistics Occupational Outlook Handbook 2012-2013 reports that the employment of market research analysts is projected to grow more than 41 percent between 2010 and 2020; even with that growth, predictions are that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions (Robert Walker, Ph.D., Computerworld, September 2013). In 2010, the median annual wage of a research analyst with a bachelor’s degree was close to $61,000.
Positions that are specifically focused on business analytics include big data analyst, data mining analyst/engineer, predictive modeler, web analyst, business intelligence consultant, Compliance Reporting, risk analyst, and much more.
The Big Data Analytics Concentration emphasizes the use of big data analytics to optimize business decisions through insight and informed decision making. An interdisciplinary application of data science tools and techniques from applied math and computer science prepare students to analyze and strategically manage large data sets. This is a technically focused program, with managerial elements. This program is for students interested in harnessing the growing sources of big data in ecommerce, social media, and on the web to solve complex business problems from various industries. Big Data Analytics provides a strong foundation in data science with newly developed courses in analytics, predictive modeling, data warehousing, multivariate statistics, and data visualization. The program requires an internship and a senior capstone project to further put learning into practice. The skills, confidence, and expertise they will learn in this class will not only help prepare students to deal with research requirements in the program, but help them succeed in an information-intensive world.
For more information about the bachelor of science in Business Administration, Big Data Analytics Concentration, call 877.523.2537 or email email@example.com.
Students will demonstrate effective written and oral communication including informed arguments, persuasion, synthesize complex data and concepts.
Students will demonstrate comfort with and ability to effectively operate in: ambiguity, complexity, uncertainty and change. Students will be adept at situational awareness. Students will understand the historical context of their culture and they will view the world from a global lens acknowledging the diversity of cultures and values. Students will demonstrate propositional thinking; they will test and iterate on ideas/solutions based upon feedback and learn from their own failures.
Students will use quantitative and analytical methods to address unstructured business problems.
Students will demonstrate ability to evaluate decisions based on an awareness of relevant stakeholders in the creation of sustainable social, environmental, and economic value.
Students will demonstrate mastery of various thinking modes, notably analytic, synthetic, convergent, divergent, creative, and critical, and when to employ each type. Student will demonstrate awareness of their own strengths and weaknesses and will seek continual improvements. Student will demonstrate both self and social awareness and management to effectively play various roles on an interdisciplinary team from leader to contributor to participant (role fluidity). These skills are essential for all leadership and management roles.
Students will identify, create, shape, and capture value through understanding economic models and the reality of industry disruption cycles.