This course is one of the foundation courses in the Applied Data Science program. It prepares the students with the fundamental knowledge on the data management. Such knowledge is critical for the students to succeed in more advanced data management courses in the program. It also exposes students to the cutting-edge data management concepts, systems, and techniques for managing a large scale of data, to ensure that students have adequate background to further explore big data analytics in the follow-up courses.
The course may be divided into three parts. (1) Fundamental of data management: data storage, file system, file format, relational data vs. semi-structured data such as XML and JSON, conceptual modeling, relational modeling, relational algebra, SQL, views, constraints, query processing and optimization. (2) Big data analytics: NoSQL, key-value and document stores, cloud data storage, distributed file system, and MapReduce. (3) Advanced topics in data management (if time permits): data cleaning, data transformation, data warehousing, and data integration.
The course will also provide students with hand-on experiences on RDBMS, e.g., MySQL, NoSQL & cloud databases such as Google Firebase, Amazon DynamoDB, MongoDB, and big data platform & software stacks, e.g., AWS EC2, Apache Hadoop, and Spark.
-- Prof. Wensheng Wu