An incremental approach for real-time big data visual analytics
Authors: Garcia, I., Casado, R. and Bouchachia, A.
Journal: Proceedings - 2016 4th International Conference on Future Internet of Things and Cloud Workshops, W-FiCloud 2016
Pages: 177-182
ISBN: 9781509039463
DOI: 10.1109/W-FiCloud.2016.46
Abstract:In the age of Big Data, the real-Time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-Time visualization of extremely large data-At-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-Time.
https://eprints.bournemouth.ac.uk/27237/
Source: Scopus
An incremental approach for real-time Big Data visual analytics
Authors: Garcia, I., Casado, R. and Bouchachia, A.
Journal: 2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW)
Pages: 177-182
DOI: 10.1109/W-FiCloud.2016.46
https://eprints.bournemouth.ac.uk/27237/
Source: Web of Science (Lite)
An incremental approach for real-time Big Data visual analytics
Authors: García, I., Casado, R., García, V. and Bouchachia, A.
Conference: The IEEE 4th International Conference on Future Internet of Things and Cloud
Dates: 22-24 August 2016
https://eprints.bournemouth.ac.uk/27237/
Source: Manual
An incremental approach for real-time Big Data visual analytics
Authors: García, I., Casado, R., García, V. and Bouchachia, A.
Conference: IEEE 4th International Conference on Future Internet of Things and Cloud
Abstract:In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.
https://eprints.bournemouth.ac.uk/27237/
Source: BURO EPrints