Skip to main content

An incremental approach for real-time Big Data visual analytics.

García, I., Casado, R., García, V. and Bouchachia, A., 2016. An incremental approach for real-time Big Data visual analytics. In: IEEE 4th International Conference on Future Internet of Things and Cloud, 22-24 August 2016, Vienna.

Full text available as:

IncrementalApproachForRealTime.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1109/W-FiCloud.2016.46


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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:incremental computation; big data; streaming processing; visualization
Group:Faculty of Science & Technology
ID Code:27237
Deposited By: Symplectic RT2
Deposited On:21 Feb 2017 14:49
Last Modified:14 Mar 2022 14:02


Downloads per month over past year

More statistics for this item...
Repository Staff Only -