A list of multiple choices is given;
<span>a)
</span>Purchase a home in the city center instead.
<span>b)
</span>Rent the apartment anyway.
<span>c)
</span>Rent the apartment with a roommate.
<span>d)
</span>Purchase a home in the suburbs instead.
The answer is (C)
John should look for an apartment and share it with a
roommate. This will bring down rent expenses to 50% as both John and the
roommate will be cost sharing the rent. If the rent expenses go down by 50%, he’ll
be able to save an additional 10% and use it for other expenses.
A workflow consists of an orchestrated and repeatable pattern of business activity enabled by the systematic organization of resources into processes that transform materials, provide services, or process information.
Create a detailed outline of what you want to achieve and sketch a workflow diagram before using workflow chart software or templates. This will help to ensure your chart is accurate and complete. Always consider your process and workflow manageability when inserting logic in your workflow chart. You can use decision symbols, connectors and text boxes. Always confirm the accuracy of your workflow chart with other stakeholders.
(If you need to know what the workflow diagrams layout is just look it up. GL.)
1. non photorealistic rendering
2. siftables
3. spherical audio
4. blu ray
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.
Learn more about anonymization here:
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