This course provides a broad introduction to the principles and practice of modern data management, with an emphasis on the relational database model. Topics in relational database systems include data modeling; the relational model; relational algebra; Structured Query Language (SQL); and data quality, transactions, integrity and security. Students will also learn approaches to building relational database application programs. Additional topics include object-oriented and object-relational databases; semi-structured databases (such as XML); and information retrieval. A database project is required.

This course provides an introduction to the major concepts and techniques used in data mining of large databases. Topics include the knowledge discovery process; data exploration and cleaning; data mining algorithms; and ethical issues underlying data preparation and mining. Data mining projects, presentations, and a term paper are required.

This course provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. First, practical techniques used in exploratory data analysis and mining are introduced; topics include data preparation, visualization, statistics for understanding data, and grouping and prediction techniques. Second, approaches used to store, retrieve, and manage data in the real world are presented; topics include traditional database systems, query languages, and data integrity and quality. Case studies will examine issues in data capture, organization, storage, retrieval, visualization, and analysis in diverse settings such as urban crime, drug research, census data, social networking, and space exploration. Big data exploration and management projects, a term paper and a presentation are required. Sufficient background in database systems and statistics is recommended.

This course starts with an introduction to advanced topics in relational databases, including their implementation and advanced SQL queries. Discussions about benefits and drawbacks of relational databases will arise, which will be the foundation for introducing new types of NoSQL databases; that is, column, key-value, and graph databases. This course will then focus on the rationale, implementation, and storing and querying capabilities of graph databases. Assignments of various kinds will be used to assess individual performance of students. Additionally, the course requires a team-based project in which students will analyze and implement state-of-the-art approaches over graph databases. Teams will present the results of their projects in class.