One of the most significant problems related to Big Data is their analysis with the use of
various methods from the area of descriptive statistics or machine and deep learning. This …

Real-time streaming data analysis and visualization are of main interest for businesses
nowadays to quickly take important decisions that could help them to enhance the decision …

Big data poses new challenges and the need for flexible, interactive, and dynamic
visualization techniques. Existing approaches, especially in enterprise data visualization …

Data streams are gaining increasing importance, particularly in applications like the Internet
of Things, Edge computing, and Industry 4.0. Analyzing these data streams accurately …

To achieve the full analytical potential of the streaming data from the internet of things, the
interconnection of various data sources is needed. By definition, those sources are …

In recent years, many deep learning methods, allowed for a significant improvement of
systems based on artificial intelligence methods. Their effectiveness results from an ability to …

Sensor networks generate substantial amounts of frequently updated, highly dynamic data
that are transmitted as packets in a data stream. The high frequency and continuous …

While in clear-cut situations automated analytical solution for data streams are already in
place, only few visual approaches have been proposed in the literature for exploratory …

ABSTRACT DIVA supports exploratory data analysis of multimedia streams, enabling users
to visualize, explore and evaluate patterns in data that change over time. The underlying …

The rapid increase of connected devices causes more and more data to be generated and,
in some cases, this data needs to be analyzed as it is received. As such, the challenge of …