"data bottleneck" is a correct and usable phrase in written English.
It is typically used to describe a situation where there is a delay or hindrance in the flow of information or data in a system or process. Here is an example: "The company's outdated technology has caused a data bottleneck, slowing down their ability to analyze market trends and make informed decisions."
But the servers were indeed an issue of the machine's design; when his firm tested them weeks later, it found a data bottleneck that would need to be fixed with a software update.
Not only would removing this data bottleneck encourage broader participation in such activities, it would also provide a reliable means to reward climate smart agriculture.
On the contrary, using a smaller pixel pitch sends more processing circuitry to the periphery of the sensor and tightens the data bottleneck between the sensor plane and the memory plane.
Mechanical Turk (MTurk) has emerged in recent years to be a promising solution to the problem of linguistic data bottleneck by providing a new paradigm for linguistic experiments, i.e., the MTurk-based experiment (Berinsky et al. 2012; Buhrmester et al. 2011; Horton et al. 2011; Mason and Suri 2012; Paolacci et al. 2010; Schnoebelen and Kuperman 2010; Sprouse 2011).
HotRail is developing products for eliminating data bottlenecks in computer networks to improve the performance of software applications running on the networks.
Nowadays, Mr. Zachary is tending Optical Networks, which helps telecommunications companies unclog the Web's data bottlenecks and deliver broadband service faster and cheaper.
But some trends are clear: unclogging the Web's data bottlenecks is becoming a priority, auctions are here to stay and businesses that generate revenue from contractual services and user fees hold more investment appeal than less-concrete models that hope to prosper by selling advertising.
Each chip will have its own built-in networking hardware and memory, reducing data bottlenecks between chips processing in parallel.
Vertical integration of the sensor plane and the processing and memory planes with a fully parallel connection eliminates data bottlenecks without compromising fill factor and pixel pitch.
Here, we present an overview of the current state of functional analysis of metagenomic sequence data, bottlenecks frequently encountered and possible solutions in light of currently available resources and tools.
We perform clustering of categorical data using the Information Bottleneck, (IB), framework at large scale.
