Dr. Colin Neill is associate professor of software engineering and systems engineering and Director of Engineering at Penn State’s School of Graduate Professional Studies. He earned his Ph.D. in software and systems engineering, M.Sc. in communication systems, and B.Eng. in electrical and electronic engineering from the University of Wales Swansea, United Kingdom.
At Penn State Dr. Neill is responsible for nationally-ranked graduate degree programs in software engineering, systems engineering, information science, and engineering management and is the founding director of the MPS in Data Analytics. He has extensive experience teaching both face-to-face and online, and is the author of over 70 research publications and two books.
We reached out to Dr. Neill to learn more about Pennsylvania State University’s online master’s degree programs in data analytics and business analytics. Read on to learn about the exciting projects their faculty are working on, the technical skills students will learn, and the best analytics websites and publications for students.
We designed the program to be meaningful to every analytics-focused professional. In the base program students can learn how to design and develop analytics systems to exploit the data deluge for their organizations, whatever the domain and application. For those specifically interested in the business domain the Business Analytics option allows for focused experiences in leveraging big data for corporate advantage. Regardless of the track taken, students have an opportunity to pursue their own interests in the elective courses, which means that the program is really applicable to everyone. Big data is everywhere, in every field, so really it behooves everyone to learn about it and learn how to exploit it.
Students will have a multitude of opportunities to work on real data. As a professionally-oriented program it is important that the student experience mimics real world scenarios closely, but on a more practical level, generating artificial data sets merely for academic purposes would be more burdensome and prone to error than using available data sets. A number of government agencies and institutions publish very large scale data sets, so we use those as sources whenever possible.
With a program drawing from three of the largest colleges at Penn State – the College of Engineering, the Smeal College of Business, and the Eberly College of Science – the array of data analytic projects our faculty work on is vast, from business analytics examples in marketing, finance and supply-chain, to engineering analytics examining things like product portfolios and system design. We also have faculty, utilizing their experiences and data from massively online open courses, working on education analytics to, amongst other things, better understand crowdsourcing in such educational settings. My own favorite example, however, is in using analytics to understand the co-evolution of complex systems and the organizations who develop and build them. We’re combining linguistic analysis with models of system evolution, system dynamics, and organizational behavior and the early results are fascinating – at least to me!
There are different sets of technical skills a professional working in data science and analytics will need, depending on their domain and task. Our program is designed so that students can tailor their program to focus on the specific skills personal to their own development. So, for those looking to design and develop analytics systems we have courses focused on the information technology – large-scale databases and warehouses, and storage schemes and tools suited to unstructured data and large-scale data processing (Hadoop, MapReduce, NoSQL,etc.). For those interested in using analytics systems we have courses focused on the types of algorithms and techniques available as well as the tools that implement them (R, SPSS, etc.).
There are important skills beyond the technical too, though. When and how to use big data approaches– strategic thinking, critical thinking, and the balance one must strike in incorporating data-driven decision-making into the overall culture and values of an organization, for example. I think we do a great job in addressing these.
I always like to recommend professional societies and their activities and publications, because these are trustworthy sources with contemporary content from experts, both academic and industrial. Two of the more dominant organizations in these fields are the IEEE and INFORMS. The IEEE has Transaction on Big Data and INFORMS has Analytics magazine. Those are two great starting points.
Don’t hesitate! The need for data-savvy managers and technologists is huge and growing. While we are generating data at ever increasing rates, without analytics-skilled professionals we can do nothing of value with it. On the flip side, the value of the information, knowledge, and even wisdom we can uncover from that data is vast. Furthermore, there are opportunities to exploit in every imaginable field – healthcare, medicine, finance, marketing, engineering, transportation, social science, you name it.