The unique reason why assembler language is preferred to high level language is that It is said to be memory efficient and it is one that requires less memory.
<h3>Why is assembly language better than other kinds of high level?</h3>
It implies means that the programs that one uses to write via the use of high-level languages can be run easily on any processor that is known to be independent of its type.
Note that it is one that has a lot of better accuracy and an assembly language is one that carries out a lot of better functions than any high-level language, in all.
Note also that the advantages of assembly language over high-level language is in terms of its Performance and accuracy as it is better than high-level language.
Hence, The unique reason why assembler language is preferred to high level language is that It is said to be memory efficient and it is one that requires less memory.
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Answer:
c. offers a great deal of network control and lower cost.
Explanation:
A network topology can be defined as a graphical representation of the various networking devices used to create and manage a network.
Compared with a star topology, a hierarchical topology offers a great deal of network control and lower cost.
Specific, Measurable, Attainable, Relevant and Timely.
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Hiding/masking personal identifiers from a data set, so that the data set can never identify an individual, even if it is correlated with other data sets is known as anonymization.
<h3>What is anonymization?</h3>
The term anonymization is known as data masking and it is the standard solution in the case of data pseudonymisation. It is generally recognised by using masking and data is de- sensitised also that privacy could be maintained and private information remains safe for the support.
Data is generally identified by using masking and data is de- sensitised also that privacy could be maintained and private information remains safe for the support.
Therefore, Hiding/masking personal identifiers from a data set, so that the data set can never identify an individual, even if it is correlated with other data sets is known as anonymization.
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