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Data Engineering Director
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M.P.A. specializing in Data Analytics & Security Policy, Columbia University

B.A. in Security Policy, Duke University

Econ One (Los Angeles, CA), 2020-Present

International Trade Centre (Geneva, Switzerland), 2018-2020

Duke Social Science Research Institute (Durham, NC), 2016-2018

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December 13, 2023

Data Anonymization: Data Security

Author(s): Miles Latham

One common consideration among our clients is data security. In addition to securely storing the data we use and closely monitoring access and permissions, we also anonymize any personal identifying information when requested. This is especially important for data in the healthcare industry which often includes personal identifying information (PII). We’re experienced anonymizing data in accordance with the HIPAA Privacy Rule, including determining which data fields need to be anonymized, and applying quantitative methods to ensure the identification risk for a final anonymized dataset is sufficiently low.

Depending on the use-case, we apply encryption algorithms such as SHA-256 that replace sensitive data fields with alphanumeric hashes. The benefits to this method are:

  1. The output hashes contain no patterns that are meaningful to the human eye and cannot be reversed with existing programs or applications. For example, the input string “John Doe” would generate the output hash “6CEA57C2FB6CBC2A40411135005760F241FFFC3E5E67AB99882726431037F908.”
  2. Every unique input string corresponds with a single unique hash output, which still allows us to group data by hashed fields if necessary. For example, we could still identify all observations associated with an individual without knowing that individual’s name or personal identifying information.

For more information about our methods and possible applications, reach out to us at dataservices@econone.com.

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