The goal of this on-going research is to elaborate DataOps as a new discipline by combining an integrated and process-oriented perspective on data with automation and methods from agile software engineering, like DevOps, to improve quality, speed, and collaboration and promote a culture of continuous improvement.
A literature review for identifying relevant application drivers, challenges and building blocks for BIA solutions suggests that particularly Internet of Things (IoT) applications drive federated analytical “ecosystem” solutions.
This paper constitutes the first steps towards an evaluation model to decide when the use of Cloud BI is appropriate by identifying and structuring consequences of Cloud computing on Service-based BI architectures.
The presented research aims at carving out viable application scenarios for Cloud BIA and at analyzing them regarding their potential business value and feasibility, and indicates that while there is an interest in Cloud-based BIA solutions, it is mostly directed towards self-contained and simple front-end driven solutions.
This work proposes a capability schema that involves actions, expected outcomes, and environmental limitations to identify fitting architecture designs and created an open online repository to collect BIA capabilities and architectural designs.
The prototype presented in this proposal constitutes a web-based software tool to support the exploration of capabilities and link them to architectural decisions in emerging IT environments.