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Data Anonymization and its Effect on Personal Privacy honors thesis presented to the School of Business, University at Albany, State University Of New York in partial fulfillment of the requirements for
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01
Start by identifying the sensitive data that needs to be anonymized.
02
Create a strategy or plan for how the data will be anonymized.
03
Implement techniques such as generalization, pseudonymization, and masking to anonymize the data.
04
Ensure that the anonymized data cannot be easily re-identified or linked back to the original data.
05
Test the effectiveness of the data anonymization process to verify that the desired level of privacy is achieved.
06
Regularly review and update the data anonymization procedures as new privacy regulations or technologies emerge.

Who needs data anonymization and its?

01
Companies and organizations that handle sensitive personal data of individuals.
02
Researchers and academics who require access to anonymized datasets for statistical analysis.
03
Government agencies and institutions involved in creating public datasets while protecting individual privacy.
04
Healthcare providers and organizations dealing with patient data to comply with privacy regulations like HIPAA.
05
Financial institutions that need to share data for analysis and research purposes while ensuring customer privacy.
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Data anonymization is the process of removing or modifying personally identifiable information from a dataset to prevent the identification of individuals.
Organizations that handle personal data are required to file data anonymization reports.
To fill out data anonymization reports, organizations need to identify the personal data collected, the purpose for collecting it, and the measures taken to anonymize the data.
The purpose of data anonymization is to protect the privacy of individuals and comply with data protection regulations.
Organizations must report the types of personal data collected, the methods used to anonymize the data, and the legal basis for processing the data.
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