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May 2019

Join BigDataStack’s Webinar on Connected Consumer Technologies for Retailers, on 29 May 2019!


Are you working in the retail-ecosystem? Are you interested in improving your consumer data analysis, real-time decision making and process improvement? Then you should join BigDataStack’s webinar on 29 May 2019, 14.00 - 15.00!

BigDataStack, a leading project where ATC and 13 other companies and research institutions are collaborating to deliver an architecture of a complete stack based on a frontrunner infrastructure management system that drives decisions according to data aspects, is organizing a series of three webinars for end-users to learn more about the technologies developed within the project and put to practice in its three industry use cases.



During the webinars, the organizations using the BigDataStack technologies in these use-cases will explain how they are using these technologies and how they will improve the end-users’ life. Furthermore, BigDataStack technology providers will explain the technologies used and will elaborate on how these technologies can be used within organizations.

BigDataStack Connected Consumer Technologies for Retailers Webinar

The first webinar will address the Connected Consumer use case application developed by BigdataStack. This use case application will provide retailers with optimal insights into consumer preferences and improve the effectiveness of marketing strategies for improving consumer shopping experience. Used by ATOS worldline, who has defined a roadmap for a major Spanish food retailer that will allow them to offer predictive shopping lists, and tailored recommendations and promotions. The webinar will be addressing challanges faced, solutions found and BigDataStack technologies to improve connected consumer experiences.

BigDataStack added-value for retailers

The data-oriented infrastructure of BigDataStack will enable:

  • Data collection, aggregation, storage and analysis, handling a multitude of heterogeneous sources which, combined, they generate data at an unprecedented rate, and BigDataStack will manage them and seamlessly analyse them for the 3 predictive services envisioned in the scenario.

  • Efficient and optimized analytics and real-time decision making enabling the development of data-based value added services such as product logistics, virtual shopping carts and predictive lists, marketing and loyalty management. These services require a real time response, for example actuation of interactive displays in stores or issuing coupons to customers’ mobile devices.

  • Process improvement (with an emphasis on product replacement) exploiting the BigDataStack process modelling and process mining outcomes. 

You can register here.




About BigDataStack

BigDataStack is a Research & Innovation Action (RIA) funded as part of the H2020 programme of the European Commission, which lasts 36 months and kicked off on the 1st January 2018. The project aims to deliver an architecture of a complete stack based on a frontrunner infrastructure management system that drives decisions according to data aspects, thus being fully scalable, runtime adaptable and high-performant to address the needs of big data operations and data-intensive applications. Furthermore, the stack goes beyond purely infrastructure elements by introducing techniques for the dimensioning of big data applications, modelling and analysis of processes as well as the provision of data-as-a-service exploiting a proposed seamless analytics framework.

ATC leads all the interaction mechanisms of the BigDataStack platform. These mechanisms will aim at:

  1. Increased and predictable performance of data operations and data-intensive applications by dimensioning them regarding the required infrastructure resources.
  2. Efficiency and agility through declarative process modelling allowing the stakeholders to specify functionality-based process models that will be turned to process analytics and mining tasks in an automated way by the modelling framework and analyzed through the data mining mechanisms.
  3. Usability and extensibility by delivering a toolkit allowing big data practitioners both to ingest their analytics tasks (through declarative methods) and to set their requirements / preferences.
  4. Exploitation through the visualization environment of the analytics outcomes and providing a complete view of the data (e.g. outcomes of incremental queries) and also of the infrastructure. ATC is responsible to deliver the Declarative process modeling framework and the Visualization framework. Furthermore, ATC leads Innovation Management supporting the project innovation strategy and exploitation activities.