DAT 211 - Data Integration and Analytics

This course examines the tools and methods that are used to integrate data from distributed systems into centralized repositories and gather insights from them. Whether the data is coming from a flat file, API, or relational database, and whether it is being streamed in real-time or loaded via large asynchronous batches, students will learn how to build data pipelines that can effectively extract, transform, and load large amounts of information between systems. After consolidating data from these various systems, students can then leverage software platforms like Tableau and Microsoft Power BI to model the data into an appropriate schema, gain insights from their data models through visualization and analytics, and even experiment with automated machine learning techniques to uncover a deeper understanding of the data and its predictive potential.

Satisfies Data Science minor requirement.
Satisfies Mathematical and Quantitative Thought requirement.

Prerequisites & Notes
DAT 153 (Database Programming) or CSC 353 (Database Systems)