I-BiDaaS: Industrial-Driven Big Data as a Self-Service Solution
The I-BiDaaS project aims to empower end-users to utilize and interact with big data technologies more easily.
Specification of an end-to-end Big Data as-a-self-service platform
This innovation corresponds to specification of an end-to-end platform for Big Data as-a-self-service, developed within the I-BiDaaS project.
ADMM Machine Learning Algorithms
This is an open-source implementation of the Alternating Direction Method of Multipliers (ADMM)[1] optimization algorithm that relies on CVXPY[2], a Python-based toolbox for
BigDataStack - High-performance data-centric stack for big data applications and operations
BigDataStack will deliver a complete high-performance data-centric stack of technologies as a unique combined and cross-optimized offering that addresses the emerging needs of data operations and applications.
DataBench Toolbox
The goal of the DataBench Toolbox is to provide a way of reusing existing big data benchmarking efforts under a common framework, providing therefore a way to select, download and homogenize technical and business indicators.
SAP Data Hub
The all-in-one data orchestration solution discovers, refines, enriches, and governs any type, variety, and volume of data across your entire distributed data landscape.