Examples of using Large volumes of data in English and their translations into Chinese
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NoSQL databases are used to store large volumes of data, such as IoT data output from various IoT devices in a variety of structures.
Large volumes of data are needed to train networks to do the most rudimentary things.
Using these very large volumes of data and very powerful computing power, we can discern patterns then test again for these patterns using new data. .
Although Bechtel can analyze large volumes of data, the quality of the data located all over the business must be improved.
Such a system would allow archivists, researchers, content creators, and others to scatter large volumes of data over the Internet.
Con Ed's investigation has involved inspecting and testing transmission equipment, and analyzing the large volumes of data.
Many groups have already begun developing high-speed grids to connect research institutions and laboratories, so that scientists can more efficiently share large volumes of data.
First, they provide scalability to store large volumes of data on commodity hardware.
These applications can also leverage Alibaba Cloud's Big Data platform DataWorks and MaxCompute for analyzing complex and large volumes of data in real-time.
During the recent Microsoft Ignite conference, Microsoft introduced a public preview of a new option for moving large volumes of data to the cloud.
Every piece of technology comes with an upfront cost, but Hadoop is much more cost effective for storing large volumes of data.
Unlike general-purpose computers and smartphones, the majority of IoT devices and sensors are not sending and receiving large volumes of data.
Pivotal boasts that Greenplum is a"best-in-class, enterprise-grade analytical database" that can perform powerful analytics on very large volumes of data very quickly.
Several database vendors have developed parallel databases that can store large volumes of data.
Photonics is the most energy-efficient and cost-effective method to transmit large volumes of data over long distances.
For these models to be statistically and operationally relevant, large volumes of data will be needed.
As an unstructured storage protocol, object storage represents a great way to store large volumes of data at a cost-effective price.
In order for these models to be statistically relevant, large volumes of data are required.
A recurring theme in these meetings was the desire to scrape large volumes of data from the web, and then to represent it visually.
It allows archivists, content creators, researchers, and many others to distribute large volumes of data over the Internet.