Data Architecture and Programming

Catalog description

We live in an age of data abundance. Vast amounts of data are being collected and analyzed to inform decision-making. Data-driven organizations depend on more than dashboards and algorithms. They need reliable data foundations: well-designed databases, clean data pipelines, reproducible transformations, and analysts who can move comfortably between business questions, data architecture, SQL, Python, and modern analytics tools. This course introduces students to the core concepts and practical skills needed to work with structured data in a business analytics environment. Students will learn the basics of data architecture, relational databases, data modeling, SQL querying, Python-based data treatment, and workflow tools used in modern analytics teams. The course is designed for MS in Business Analytics students who may not all have technical backgrounds. The emphasis is practical and applied. Students will learn how data is structured, how it moves through an organization, how it is cleaned and transformed, and how it can be prepared for analysis, visualization, and decision-making. By the end of the course, students should be able to understand common data architectures, write intermediate SQL queries, perform basic-to-intermediate data transformations in Python, and explain how modern data tools fit into an analytics workflow.