How long does it take your new employees to start adding value? How well are your current employees doing on the job? Can your organization do more to support the training & development of your employees? In this project, students in the McMaster University Centre for Continuing Education Human Resources Management program will provide actionable training & development recommendations, processes, or high-level design to enhance the performance of both new and experienced employees.

The capstone course is part of the Big Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. Students apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

This course is part of the Big Data Programming and Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course is designed to present the fundamental concepts and theories in Data Analytics and promote the application to the workplace and professional practice. Students begin with an exploration of MongoDB which is a document database with scalability and flexibility for queries and indexing, and progress to the ELK stack – a technology stack used for logging with different components, such as Elasticsearch, Logstash, and Kibana. Course activities will include instructor presentations, required readings and experiential learning activities (i.e. case studies, group discussions, projects, etc.).

This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course explores the importance of managing data as an enterprise asset and the processes and components required in terms of the acquisition, storage, sharing, validation and accessibility of data for addressing business problems. An examination of Database Management Systems, database architectures (structured and non-structured) the differences between OLTP (Online transaction processing) OLAP (online analytical processing) as well as the administrative processes (Data Governance) that guide the data lifecycle will be a focus.