Big Data Analytics for Improved Care Delivery in the Healthcare Industry (Solved)
computer science
Description
Agile Big Data Analytics for Web-Based
Systems: An Architecture-Centric Approach
Hong-Mei Chen, Rick Kazman, Senior Member, IEEE, and Serge Haziyev
Abstract—This article contributes an architecture-centric methodology, called AABA (Architecture-centric Agile Big data Analytics), to
address the technical, organizational, and rapid technology change challenges of both big data system development and agile delivery
of big data analytics for Web-based Systems (WBS). As the first of its kind, AABA fills a methodological void by adopting an
architecture-centric approach, advancing and integrating software architecture analysis and design, big data modeling and agile
practices. This article describes how AABA was developed, evolved and validated simultaneously in 10 empirical WBS case studies
through three CPR (Collaborative Practice Research) cycles. In addition, this article presents an 11th case study illustrating the
processes, methods and techniques/tools in AABA for cost-effectively achieving business goals and architecture agility in a large scale
WBS. All 11 case studies showed that architecture-centric design, development, and operation is key to taming technical complexity
and achieving agility necessary for successful WBS big data analytics development. Our contribution is novel and important. The use of
reference architectures, a design concepts catalog and architectural spikes in AABA are advancements to architecture design
methods. In addition, our architecture-centric approach to DevOps was critical for achieving strategic control over continuous big data
value delivery for WBS.
