E2Data For Real

Our industry partners ensure that E2Data stays focused on what matters: enabling companies to meet their SLAs and improve their bottom line. Our use cases come from the following four domains:


It is necessary to improve the predictive capability of a hospital readmission risk prediction algorithm. To achieve this, the patient discharge profile is enhanced with profiles of highly correlated patients (in terms of recent hospital activity). The patient correlations are established based on their medical conditions. The algorithmic solution enters into time sensitive matrix calculations which need to be accelerated appropriately.


Fintech (Natural Language Processing)

Text processing aims to extract knowledge :  reasoning, correlation with event streams, sentiment analysis, summarization, data cleansing, interpretation and organization of contents are indicative useful applications, which can be useful in several business domains (finances, tourism, telecoms, marketing, IoT). In many cases, such processing  must deliver results under strict time constraints; however,  the engaged algorithms are complex and data volumes can be extremely high. In E2Data, we focus on accelerating critical algorithmic code to perform fuzzy matching among words and expressions; these algorithms are falling in the critical path in the knowledge extraction process and, therefore, acceleration is considered as a solution towards enhanced performance.

Green Building Infrastructure

The Green Buildings use case provides a scenario for achieving energy efficient buildings based on analytics of real time stream data derived from Internet of Things (IoT) deployed sensors in a number of public schools. In this context, big data analytics algorithms and techniques will be deployed in E2Data in order to achieve higher levels of computational efficiency that will enable processing pipelines for the real-time monitoring of the building’s energy behaviour.


Security and biometric recognition

Biometric authentication, using facial recognition, is fast becoming a mainstream method of authenticating customers for high value transactions, such as the creation of Bank Accounts, issuing of Travel Visas and unmanned border crossing by pre-registered users. Such processes are coupled with tight SLAs to ensure the best possible user experience. E2Data will both optimize the cost base of the platform and automate the performance optimization of code, something that until now has required skilled, and expensive, developers.

This project has received funding from the European Union's Horizon H2020 research and innovation programme under grant agreement No 780245.

E2Data is part of the Heterogeneity Alliance