Examples of using The volume of data in English and their translations into Chinese
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The volume of data had also increased, due in part to the  significant expansion of  emergency and relief operations by the  Office for the  Coordination of  Humanitarian Affairs.
The volume of data within a typical transmission should match the  packet size that the  chosen protocol can accommodate.
By 2020, the volume of data collected will be 40 zettabytes, which is every single grain of  sand on earth times 75.
The volume of data stored to support a big data  application can be several factors of  ten larger than all of  your operational data  combined.
When aggregating keys with high cardinality(such as URLs), the volume of data is not reduced by much(less than twofold).
The volume of data would be very large, with a tendency to become larger, especially if your site monitors several aspects of  its visitors' behavior.
For instance, the  sheer number of  sensors and the volume of data transfer have enormous software and hardware implications.
When aggregating a large quantity of  keys, the volume of data is not reduced, and aggregation is useless.
In the  first studies the volume of data was unfortunately too small for it to be possible to either confirm or reject Petersson's model.
According to a recent Computerworld study among 300 of the  world's largest enterprises, the volume of data is expected to increase by about 60 percent in 2013.
In addition, if a specific data  can be considered as a Big Data  or not, it depends on the volume of data.
The volume of data used in business, research and technological development is massive and continues to grow.
There is a popular opinion that in order to effectively calculate statistics, you must aggregate data,  since this reduces the volume of data.
The volumes of data generated today have made establishing secondary data  centers cost-prohibitive, too: a further factor driving companies to the  cloud.
The volumes of data generated today have made establishing secondary data  centers cost-prohibitive, too: a further factor driving companies to the  cloud.
The volumes of data we generate, and the  insights we extract from this data,  are expanding exponentially.
Getting the  storage platform right is essential because the volumes of data involved are significant.
IoT networks consist of  numerous sensors that continuously collect enormous amounts of data,  exponentially greater than the volumes of data collected for big data  analytics.
But aside from huge data-generating companies, the  majority of  companies don't acquire the volumes of data required to properly train AI algorithms.