Abstract
Agile development for big data analytics has become the new normal. However, research questions remain: 1) how should a big data system be designed and developed to effectively support advanced analytics? and 2) how should the agile process be adapted for big data analytics development? This article contributes an Architecture-centric Agile Big data Analytics (AABA) development methodology evolved and validated in 10 case studies through Collaborative Practice Research. Our studies showed that architecture agility is the key for successful agile big data analytics development. Employing an architecture-centric approach, the AABA methodology integrates the Big Data system Design (BDD) method and Architecture-centric Agile Analytics with architecture-supported DevOps (AAA) model for effective value discovery and rapid continuous delivery of value. The uses of a design concepts catalog and architectural spikes are advancements to architecture design methods that have proven to be critical to agile big data analytics development.
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