BUS 282 W — Leading Data-Driven Organizations
From simple data analytics to artificial intelligence, leading an organization utilizing data is challenging. With the recent explosion in the availability of tools, training, and approaches, there are many options and factors to consider. This course will begin with a discussion of the principles and basic components of a data-driven environment. We will then cover such topics as calculating the value of data, data collection strategies (cloud and on-premise), data engineering, data workforce development, machine learning project selection, and implementation and deployment. With a view toward educating leaders, lectures and assignments will focus on practical applications including AI-enabled product development, designing a data management ecosystem, and automating organization performance metrics such as OKRs (objectives and key results), KPPs (key performance parameters), and others. By the end of the course, students will understand the architectural requirements for creating production-quality data products and services, and will be able to build and deploy a simple end-to-end data-focused project.
Students should have knowledge of basic math and exposure to basic computer programming concepts, such as variables and control flow. It would be helpful but not required to have some familiarity with data analysis concepts such as data visualization, statistics, exploratory analysis, or machine learning.