Examples of using Data cannot in English and their translations into Chinese
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Political
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Ecclesiastic
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Programming
Data cannot be wrong.
In other words, your data cannot be misused by third parties.
Data cannot be deleted or altered.
This means that your data cannot by misused by third parties.
Data cannot be transferred directly into the root directory;
This ensures that biometric data cannot be accessed or used outside the card.
The data cannot be changed or modified due to security protocols.
When the amount of data is tremendous,it is obvious this data cannot be dealt with on any single machine.
The data cannot be wrong.
In contrast to passwords, badges, or documents, biometric data cannot be forgotten, exchanged, and cannot be forged.
This data cannot be deleted.
This data cannot be used to identify any visitor individually.
This means that your data cannot be used inappropriately by third parties.
This data cannot be used to identify visitors individually.
€¢ Limited monitoring tools and data cannot fully reflect the hydraulic status of the pipeline network.
The data cannot be erased or altered.
This is because the semi-structured or unstructured data cannot easily be joined with the data from other enterprise data sources to deliver insight.
Big data cannot solve everything.
For example, data cannot be stored neatly on a disk.
Big data cannot solve everything.
Other data cannot be stored effectively.
Big data cannot predict the future.
Game save data cannot be copied to microSD card.
Two data cannot be stored in the same slot in array.
Ensure that data cannot be amended between the browser and server.
ROM data cannot be updated arbitrarily, but can be read at any time.
These data cannot be traced back to a certain person and can be deactivated in the Display settings at any time.
However, this data cannot be attributed to a particular person, which means that the user/ individual account remains anonymous.
While Big Data cannot completely prevent such risks, it can identify those at early stages and prevent further development into risky paths.
Even Apache Spark jobs where the data cannot be completely contained within memory tend to be around 10 times faster than their MapReduce counterpart.