This report is the first version of a summary of project management techniques to be used in running BigDataStack, including procedures for communication, documentation, deliverables review, procedures to control project progress, and risk management.
This is the first deliverable of a series of deliverables (i.e. updated versions will follow) that identifies and specifies the technical requirements for BigDataStack environment and tracks them during the project lifecycle.
This is the second version of a series of three deliverables specifying the stakeholder as well as technical (software and technology) requirements for BigDataStack. In the requirements analysis shown in this document, a top-down approach is taken with respect to the user requirements, which have been collected through the BigDataStack use case providers. This is complemented with a bottom-up approach aiming to identify, collect, and analyse the rest of stakeholder requirements as well as technical requirements from BigDataStack technology providers.
In the requirements analysis presented in this document, a top-down approach is taken with respect to the user requirements, which have been collected through the BigDataStack use case providers. This is complemented with a bottom-up approach aiming to identify, collect, and analyse the rest of the stakeholder requirements as well as technical requirements from the BigDataStack technology.
This deliverable is a refinement of the key functionalities of the overall architecture, the interactions between the main building blocks and their components, as they were described in the previous version of the architecture (Deliverable D2.4 - Conceptual model and Reference architecture).
This deliverable presents Scientific Report and Prototype Description for the work carried out in the first year of the BigDataStack project, related to the so-called Data-Driven Infrastructure Management capability of the BigDataStack platform. The document shows how the implementation of the solution is planned to be delivered following an incremental and iterative methodology, having cycles of implementation and experimentation.
The Data as a Service block presents a fine set of data services which can be mapped to the major phases of Big Data processing. The architecture and the design of these data services are achieved through dedicated techniques, contextualized in the BigDataStack environment in order to run on top of the data-driven infrastructure management system and provide the required data services.
BigDataStack delivers a complete high-performant stack of technologies addressing the needs of data operations and applications. BigDataStack’s holistic solution incorporates approaches for data-focused application analysis and dimensioning, and process modelling towards increased performance, agility and efficiency. A toolkit allowing the specification of analytics tasks in a declarative way, their integration in the data path, as well as an adaptive visualization environment, realize BigDataStack’s vision of openness and extensibility.
BIGDATASTACK has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779747. The content of this website does not represent the opinion of the European Commission, and the European Commission is not responsible for any use that might be made of such content.