BigDataStack: The Innovative, High-Performing, and Data-Centric Stack for Big Data Applications and Operations

Today’s data-driven industrial revolution calls for big data technologies to unlock the potential in various application domains, and this is what BigDataStack project aims to provide.

A new high-powered stack of technologies, BigDataStack, kicked off this January 2018. Heading the multinational, strong consortium of 14 partners, is IBM Haifa, Israel with a focus on addressing the emerging needs of providing fully efficient and optimised cluster management for data operations and data-intensive application.

The project, funded under the European Commission Horizon 2020 Work Programme, will present in 36 months, a set of prototypes demonstrating a complete high-performance data-centric stack of technologies.

Eliot Salant, BigDataStack’s project coordinator, with a proven track record on managing large-scale infrastructure projects such as this, highlights that: “BigDataStack will provide a complete infrastructure management system that will base the management and deployment decisions on data aspects thus being fully scalable, runtime adaptable and high-performing for big data operations and data-intensive applications”.

BigDataStack: a complete suite for big data analytics

Enhanced infrastructure capabilities are a must in data centres.  BigDataStack infrastructure management system goes beyond storing, processing and offering data to enabling optimum data service provisioning by turning the underlying infrastructures to enhanced, data-driven, and data-oriented environments.

BigDataStack will promote automation and quality and ensure that the provided data are meaningful, of value and are relevant. This is achieved through its Data as a Service offering that addresses the complete data path with approaches for data cleaning, modelling, semantic interoperability, and distributed storage. BigDataStack also introduces a pioneering technique for seamless analytics complemented with a real-time cross-stream processing engine to analyse data in a holistic fashion across multiple data stores and locations, handling analytics on both data in flight and at rest.

BigDataStack’s holistic solution incorporates approaches for data-focused application analysis and dimensioning, and process modelling towards increased performance, agility and efficiency. There will be a toolkit allowing the declarative specification of analytics tasks, their integration in the data path, as well as an adaptive visualization environment, allowing BigDataStack to realize its vision of openness and extensibility.

Commercial use cases

To enable data operations and data-intensive applications to fully exploit the sustainability of BigDataStack and take full advantage of the developed technologies, the consortium has brought on board three use cases that will exhibit their applicability through:

  1. Real-time ship management: The algorithms will optimize and help cut costs on maintenance and spare parts inventory planning and dynamic routing. These predictions will be estimated and provided to DANAOS, a leading international maritime player with more than 60 container ships.
  2. Connected consumer: This will provide retailers with optimal insights into consumer preferences and improve the effectiveness of marketing strategies for improving consumer shopping experience. This will be used by ATOS, which is currently defining a roadmap for a major Spanish food retailer that will allow them to offer predictive shopping lists, and tailored recommendations and promotions.
  3. Intelligent multi-channel banking: A multi-channel scenario will be developed and adopted by ATOS which will facilitate data analytics-powered intelligent banking, providing a 360-degree view of the customer and personalized services. This is expected to increase business agility and reduce operational costs.

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