Introducing Data Science to Undergraduates through Big Data: Answering Questions by Wrangling and Profiling a Yelp Dataset

Date
2017-01-04
Authors
Jensen, Scott
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Abstract
There is an insatiable demand in industry for data scientists, and graduate programs and certificates are gearing up to meet this demand. However, there is agreement in the industry that 80% of a data scientist’s work consists of the transformation and profiling aspects of wrangling Big Data; work that may not require an advanced degree. In this paper we present hands-on exercises to introduce Big Data to undergraduate MIS students using the CoNVO Framework and Big Data tools to scope a data problem and then wrangle the data to answer questions using a real world dataset. This can provide undergraduates with a single course introduction to an important aspect of data science.
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Big Data, Data Science, Data Wrangling, Data Profiling, Education
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