mehrantjb / asu-cse511-data-processing-at-scale

ASU-CSE511-Data Processing at Scale

Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This course delves into new frameworks for processing and generating large-scale datasets with parallel and distributed algorithms, covering the design, deployment, and use of state-of-the-art data processing systems, which provide scalable access to data. Specific topics covered include:

• Efficient query processing
• Indexing structures
• Distributed database design
• Parallel query execution
• Concurrency control in distributed parallel database systems
• Data management in cloud computing environments
• Data management in Map/Reduce-based
• NoSQL database systems

Learners completing this course will be able to: -Differentiate among major data models such as relational, spatial, and NoSQL

• Perform queries (e.g., SQL) and analytics tasks in state-of-the-art database systems
• Apply leading-edge techniques to design/tune distributed and parallel database systems
• Utilize existing NoSQL database systems as appropriate for specified cases
• Perform database operations (e.g., selection, projection, join, and group by) in state-of-the-art cluster computing systems such as Hadoop/Spark
• Perform scalable data processing operations (e.g., selection, projection, join, and group by) in cloud computing environments, including Amazon AWS