Please use this identifier to cite or link to this item:
Introducing Data Science to Undergraduates through Big Data: Answering Questions by Wrangling and Profiling a Yelp Dataset
|Title:||Introducing Data Science to Undergraduates through Big Data: Answering Questions by Wrangling and Profiling a Yelp Dataset|
|Issue Date:||04 Jan 2017|
|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.|
|Rights:||Attribution-NonCommercial-NoDerivatives 4.0 International|
|Appears in Collections:||Big Data and Analytics: Concepts, Methods, Techniques and Applications Minitrack|
Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.