COMM 392 - Intro to Data Management and Analytics

COMM 392 - Intro to Data Management and Analytics

A term adjunct position is open at the Smith School of Business for an instructor to teach at our main campus in Kingston, in a lecture-style undergraduate course in the Commerce program. The position is to teach Intro to Data Management and Analytics for Business – COMM 392 in the winter term. There are two sections available to teach. Teaching one (1) of these sections of COMM 392 will entail teaching 3 hours per week, in two 1.5-hour sessions (24 classes in a term), from January to April 2027. The successful applicant will be required to teach 100% of one or more sections of COMM 392, with a maximum enrollment of 55 students.

COMM 392 – Introduction to Data Management and Analytics

This course provides an introduction to data management and analytics for business. The course will present a systematic view of analytics with a key focus on using data for business intelligence and descriptive analytics as well as an overview of predictive analytics and how they are used by businesses for creating a competitive advantage.

The course emphasizes the managerial aspects of analytics along with applications and implementation challenges, rather than technical issues (e.g. coding).

The course will also focus on how to understand and manage data as an asset that is at the core of value creation in today's digital age, with emphasis on technical aspects such as data structure, data models, and data preparation and exploration, as well as management aspects such as data reliability and quality.

Students will learn and apply relevant business intelligence and analytics concepts for solving various types of business problems using real data and practical business cases.

Learning Outcomes

1. Organize data for answering business questions through applications involving data modeling, extraction, querying, and transformation.
2. Describe issues that can arise with data and the resulting models and implement techniques to address them effectively.
3. Explain how organizations can use business intelligence and data analytics, AI, and machine learning for operational and strategic purposes.
4. Use technology tools to perform descriptive data analytics, including data preparation, modeling, and visualization.
5. Build, train, test, evaluate, and deploy a machine learning model using graphical interface tools, and choose between competing models.
6. Communicate analytics results to managers and to a general business audience.

The open sections for COMM 392 have been scheduled in the Winter term as follows:

Sections

• 001 – Tue 10:00 AM to 11:30 AM / Thur 08:30 AM to 10:00 AM
• 002 – Mon 10:00 AM to 11:30 AM / Wed 08:30 AM to 10:00 AM

Qualifications

Qualifications include a Master’s degree or PhD; several years of related experience; and experience teaching university courses.

Compensation

The salary for a term adjunct teaching one section of a course in our Commerce program is $13,856 (excluding vacation pay). This salary is pro-rated based on course credit.

Smith School of Business

Smith School of Business is one of the world’s premier business schools, with an outstanding reputation for innovation and quality. Our MSc and PhD programs in Management attract highly qualified research-oriented students in many fields of study. Our undergraduate Commerce program has among the highest entrance standards in Canada, and is widely viewed as the country’s best undergraduate business program. Queen’s has gained international recognition for its MBA and executive education programs, and is fully accredited by AACSB and EQUIS. The learning environment at Queen’s is supported by outstanding computing, library, and research facilities.

Smith School of Business has a number of established research centres and institutes that support a wide range of research interests, including the Institute for Sustainable Finance, Centre for Entrepreneurship, Innovation and Social Impact, and the Scotiabank Centre for Analytics & AI. It is a part of a world-class ecosystem in Analytics and AI that was awarded the 2020 Informs UPS George D. Smith Prize for Innovation in Higher Education. Smith is a member of the Council of Business & Society , an organization of leading business schools with global reach committed to positively changing the world at the crossroads of business, society, and the planet. We also have substantial ties to industry, government, non-profits, and other higher education institutions, including a large network of industry experts on the Smith Advisory Board , to enhance the impact of research, teaching, and service.

Smith School of Business is committed to cultivating a vibrant, diverse and inclusive academic and work environment rooted in a culture of mutual respect and equity, such that all members of our community feel safe, possess a strong sense of belonging, and are empowered to thrive.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to declare their COVID-19 vaccination status and provide proof that they were fully vaccinated or had an approved accommodation to engage in in-person University activities. These requirements were suspended effective May 1, 2022, but the University may reinstate them at any point.

Equity Statement

The University invites applications from all qualified individuals. Queen’s is strongly committed to employment equity, diversity and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous people, women, persons with disabilities, and 2SLGBTQ+ persons. In accordance with Canadian immigration requirements, Canadian citizens and permanent residents of Canada will be given priority, including any qualified individuals who have a valid legal work status in Canada. Applications from all qualified candidates will be considered in the applicant pool.

In addition, the impact of certain circumstances that may legitimately affect a nominee’s record of research achievement will be given careful consideration when assessing the nominee’s research productivity. Candidates are encouraged to provide any relevant information about their experience and/or career interruptions.

The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes into account an applicant’s accessibility needs. If you require accommodation during the interview process, please contact .