Software Engineering for Real-Time NoSQL Systems-centric Big Data Analytics

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

William Clark (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Recent advances in Big Data Analytics (BDA) have stimulated widespread interest to integrate BDA capabilities into all aspects of a business. Before these advances, companies have spent time optimizing the software development process and best practices associated with application development. These processes include project management structures and how to deliver new features of an application to its customers efficiently. While these processes are significant for application development, they cannot be utilized effectively for the software development of Big Data Analytics. Instead, some practices and technologies enable automation and monitoring across the full lifecycle of productivity from design to deployment and operations of Analytics. This paper builds on those practices and technologies and introduces a highly scalable framework for Big Data Analytics development operations. This framework builds on top of the best-known processes associated with DevOps. These best practices are then shown using a NoSQL cloud-based platform that consumes and processes structured and unstructured real-time data. As a result, the framework produces scalable, timely, and accurate analytics in real-time, which can be easily adjusted or enhanced to meet the needs of a business and its customers.

Additional Information

Publication

Thesis

Language: English

Date: 2020

Keywords

Big Data Analytics, DevOps, DataOps, NoSQL, Machine Learning, Containers, Cloud Services

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