This course provides an in-depth exploration of database security, focusing on defining and implementing views for secure data access. Students will learn how to apply dynamic authorization techniques through cascading grant and revoke policies, and specify semantic integrity rules essential for maintaining security and consistency within distributed database systems.

This course delves into the critical aspects of query optimization in databases, focusing on the motivation behind optimizing queries, evaluating the cost-effectiveness of various query plans, and understanding the steps involved in the optimization process. Students will learn to calculate optimization costs and decompose SQL queries into efficient, optimized query trees, enhancing overall database performance.

This module delves into distributed query optimization techniques, introducing key methodologies to improve performance in distributed systems using cost models and heuristics for near-optimal query plans. Learners will gain practical skills in query optimization, leveraging the semi-join algorithm. Learners will also gain experience in another popular large-scale data approach embodied in MapReduce supported by the Hadoop Distributed File System (HDFS) to efficiently process large datasets. Through hands-on exercises, students will practice writing HDFS code for data storage and manipulation, focusing on data compression and decompression, and employ advanced MapReduce patterns for optimal data processing..