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Mohamed Sarwat and Ming Zhao
Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This specialization delves into new frameworks for processing and generating large-scale...
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Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This specialization delves into new frameworks for processing and generating large-scale datasets with parallel and distributed algorithms. Courses cover the design, deployment and use of state-of-the-art data processing systems, which provide scalable access to data. All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization.
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What's inside

Five courses

NoSQL Database Systems

(0 hours)
Unlike traditional relational database management systems, NoSQL databases can store unstructured data. They meet the performance, scalability, and flexibility needs of data-intensive applications and are essential for big data processing. This course covers key NoSQL data management systems topics, including key-value stores, graph databases, and document databases.

Distributed Database Systems

The increased capabilities of a collection of logically interrelated databases distributed over a computer network enable scalable data processing. This course addresses the components of these systems, covering distributed database architectures, distributed data storage and indexing, distributed and parallel query processing/optimization, and concurrency control in distributed Parallel Database Systems.

Data Management in the Cloud

(0 hours)
Ubiquitous, on-demand network access to shared pools of configurable computing resources ideally requires minimal management effort or service provider interaction. This course covers the essential characteristics of data processing in the cloud, service and deployment models, and key components of implementing Amazon Web Services, as well as constructing Hadoop clusters and performing MapReduce operations.

Core Database Concepts

This course introduces the world of database systems, providing a foundation for mastering data modeling and information extraction using database management systems. Topics covered include database design/modeling, data storage and indexing, query processing/optimization, transaction management, database security, and data analytics.

Big Data Tools

(0 hours)
Systems that perform big data analytics require highly distributed architectures and new levels of memory and processing power. This course covers main topics associated with systems such as Hadopp MapReduce, Apache Spark, and Graph Processing Engines.

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