Abstract: With the emergence of big data as a strategic weapon in business, the need for hands-on activities in undergraduate courses is essential for preparing the next wave of technical talent. As the availability of programs in data analytics and data science grows based on market demands, the need for foundational technical skills is important to equip graduates for readily available entry level jobs in the field. While the available literature contains elements of application of big data into the classroom, mainstream tools like Apache Hadoop have not been readily addressed. This paper evaluates two different methods of providing students exposure to Hadoop through either an on-premises cluster or virtual machines. A proposed methodology is provided for students to gain hands-on experience through lab exercises, assessed through pre- and post-quizzes to test understanding. In addition, student work is assessed for application and analysis in a Business Intelligence and Big Data undergraduate course. This work contributes to the information systems (I.S.) community by providing foundational elements essential for integrating software tools such as Hadoop, Hive, and Spark into coursework.
Keywords: Big data, HADOOP, Business intelligence, Curricula, Pedagogy, Data analytics
Download this article: ISEDJ - V17 N4 Page 42.pdf
Recommended Citation: Podeschi, R., DeBo, J. (2019). Integrating Big Data Analytics into an Undergraduate Information Systems Program using Hadoop. Information Systems Education Journal, 17(4) pp 42-50. http://isedj.org/2019-17/ ISSN: 1545-679X. (A preliminary version appears in The Proceedings of EDSIGCON 2018)