Database Systems and Data Preparation

This course will provide a foundation in discrete mathematics, data structures, algorithmic design and implementation, and computational complexity. Students will be introduced to relational databases focusing on learning SQL with the Postgres database. Topics include schemas, indexes, query efficiency, server-specific navigation functions, and queries with grouping, ordering, sorting, collapsing, and joins. Distributed data storage and processing techniques for parallel processing (MapReduce) and their implementation (Hadoop) will be covered, as well as strategies for accessing unstructured data and handling streaming data. In addition to the technical foundations, data privacy, data accountability, data protection laws (e.g., GDPR, etc.), and ethics of collecting and storing large amounts of data will be discussed in class. Time permitting, issues around synthetic data and data perturbation that prevents the identification of individuals may be addressed. Required Background:Python programming skills, experience in data manipulation using pandas. Prior SQL experience is encouraged but not required