streaming data processing software typically analyzes the data incrementally, and performs real-time aggregation and correlation, filtering, or sampling. The stream is often stored as well, so ...

In light of the substantial impact of sampling in Twitter data stream, this article explores a combination of spectral clustering, locality-sensitive hashing (LSH), latent Dirichlet allocation (LDA) ...

Volume is the most prominent of big data’s “3 Vs.” Yet, the “big” in big data analysis is often a misnomer. Most big data analysis doesn’t look at a complete, large dataset. Instead, it looks at a ...

As a streaming data warehouse, Kinetica processes data in real time and unifies analysis of different data formats, such as relational, geospatial, graph, and time series data at scale.

Abstract: This paper proposes SSketch, a novel automated computing framework for FPGA-based online analysis of big data with dense (non-sparse) correlation matrices. SSketch targets streaming ...

A data streaming solution must account for speed, security, scaling and more if it’s to provide the productivity, service and information it’s designed to deliver.

Statistics is the collection, description, and analysis of data, and the formation of conclusions that can be drawn from them.

With advancements in AI and machine learning, the analysis of data streams will become even more sophisticated, offering deeper insights and more predictive capabilities. As we look to the future, ...