Proceedings of the 50th Hawaii International Conference on System Sciences | 2017 Introducing Data Science to Undergraduates through Big Data: Answering Questions by Wrangling and Profiling a Yelp Dataset Scott Jensen Lucas College and Graduate School of Business, San José State University
[email protected] Abstract formulate data questions, and domain business There is an insatiable demand in industry for data knowledge. In a recent study of analytics and data scientists, and graduate programs and certificates science programs at the undergraduate level, are gearing up to meet this demand. However, there Aasheim et al. [1] found that data mining and is agreement in the industry that 80% of a data analytics/modeling were covered in 100% of such scientist’s work consists of the transformation and programs. Of the four major areas reviewed, the area profiling aspects of wrangling Big Data; work that least frequently covered was Big Data. However, may not require an advanced degree. In this paper Big Data is the fuel that powers data science. we present hands-on exercises to introduce Big Data Undergraduate students could be introduced to data to undergraduate MIS students using the CoNVO science by learning to wrangle a dataset and answer Framework and Big Data tools to scope a data questions using Big Data tools. Since a key aspect of problem and then wrangle the data to answer data science is learning to decide what questions to questions using a real world dataset. This can ask of a dataset, students also need to learn to provide undergraduates with a single course formulate their own questions.