"Bd4nrg Query Engine – Intuitive, Efficient and Federated Querying on Big Data"

Abstract

Due to the rapid development of Internet of Things (IoT) technology during the last decade, there has been recorded a significant growth in the size of data collected by data warehouses, especially on the ones connected to sensors and meters on the energy sector. Querying such data, gathered by heterogeneous data sources is a complicated task in terms of space allocation, scalability, and integration. Big data analytics methods try to address the problem of querying big data by bringing together different data sources of different formats with a high level of abstraction. This paper presents a query engine that, on the one hand addresses the problem of querying big data stored on different and heterogeneous databases and on the other hand, simplifies the steps needed by the user for defining and executing queries on the aforementioned databases through an intuitive and easy to use interface, so as to facilitate high level analytical services. Particular attention is given to securing the tool by employing access resource management thus preventing unauthorized users from accessing the requested resources.