Data Analytics

This course provides a high-level, but rigorously comprehensive, understanding of business-focused data analytics, with special consideration given to the topics of data engineering and architecture, data science, and digital transformation. This course would be suitable for those with an immediate need or future desire to use data analytics in their workplace. However, the class will hold value for undergraduate and graduate students alike. Although the class is geared towards the non-technical student, technologists will also benefit from this class as we approach analytics from an architectural and management perspective. By the end of the course, students should be able to understand the various types of analytics and the value of each; become familiar with the most popular tools used for descriptive analytics; gain a high-level understanding of data science and analytics concepts; and be able to effectively convey data engineering and information quality concepts to peers and senior executives.

1. Understand the various types of analytics and the value of each.
2. Be knowledgeable on the most popular tools used for descriptive analytics
3. Understand (from a very high level) data science and analytics concepts such as machine learning, decision trees, clustering, etc.

Beginning-to-mid career business person, beginning their journey in data analytics, but the class will benefit students as well.

No required textbook. - will use websites, etc.

Faculty