Answer:
C) until the message has been communicated
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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Ethics:
- to ensure that privacy will not be lost.
-ensuring personal information is not lost
-information in the accountings will not be submitted or shared with anyone
-information will be saved and viewed by the business.
- The business will not falsely make the accountings.
Answer:
Explanation:
The following Python program uses a combination of dictionary, list, regex, and loops to accomplish what was requested. The function takes a file name as input, reads the file, and saves the individual words in a list. Then it loops through the list, adding each word into a dictionary with the number of times it appears. If the word is already in the dictionary it adds 1 to its count value. The program was tested with a file named great_expectations.txt and the output can be seen below.
import re
def wordCount(fileName):
file = open(fileName, 'r')
wordList = file.read().lower()
wordList = re.split('\s', wordList)
wordDict = {}
for word in wordList:
if word in wordDict:
wordDict[word] = wordDict.get(word) + 1
else:
wordDict[word] = 1
print(wordDict)
wordCount('great_expectations.txt')
