TNDY 405I: Data Analytical Tools, Technologies, and Applications Across the Disciplines
Brian Hilton, PhD and Hovig Tchalian, PhD
Students in the TNDY Big Data Analytics course listen to Professor Brian Hilton describe GIS analytics.
Each Tuesday afternoon, 16 students representing eight different programs at CGU and four students from other Claremont schools grapple with issues around big data and what it means for research and inquiry. TNDY 405I: Data Analytical Tools, Technologies, and Applications Across the Disciplines, taught by Brian Hilton (CISAT) and Hovig Tchalian (Drucker), provides students with a deep introduction to different analytical tools, experience using the tools to gather and analyze data, and a lens on structured and unstructured sources of data. They also address how to manage big data projects and big data analytics research. Together, these approaches give students a holistic perspective on Big Data.
TNDY 405I covers the basics of Big Data, static and dynamic data, geospatial analysis, data and text mining, sentiment analysis, and visualization. Students use tools such as the Microsoft Big Data Platform Azure and it’s Hadoop cluster HDInsight, ArcGIS, and Tableau during class, and can draw on these for their final projects. Alongside these tools and methods of analysis, students confront the changing nature of inquiry resulting from Big Data. Early in the semester, discussions about Big Data as a source led to a discussion of what this means for Psychology research, a field used to sampling a population in its studies. Given sensitive demographic data that can be captured in this environment, students debated how to protect individuals and consider issues of privacy in this data environment. “The nature of data is changing,” Tchalian said. “Big Data allows you to see relationships not seen in a population sample. It requires you to ask other types of research questions.”
Through case studies, students learn how companies are using Big Data. Recently, students examined Volkswagen’s use of Big Data. Volkswagen opened a Big Data Lab in Munich in the autumn of 2014, and is using research from this lab for predictive marketing, data analysis about its networked vehicles, and other business strategies. Yet the strong privacy movements in Germany require Volkswagen to balance the value of their research with protection of customer data. From such case studies, students can translate real-world applications of Big Data analytics to their own projects.
One of the expectations Hilton and Tchalian have for students is to move beyond approaching Big Data in terms of collection and analysis to consider the applications and interpretations of Big Data. In turn, they are developing responsible, thoughtful researchers who will use this data environment to examine real-world problems and develop solutions. Hilton said, “Our hope for students is that they learn more about Big Data, that they understand that the paradigm for doing research is changing, and that they take a more holistic view of Big Data.”