Clear up PII in ODM

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Aug 6th, 2022
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How to clear up PII in ODM

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foreign itamp;#39;s 11 30. please welcome to the stage everybody Rachel on a Jamal who are going to walk us through pii detection at scale on the lake house take it away [Applause] so good morning everyone uh suckers for punishment huh keynote speech and now you want to learn about pii so uh so personal information how can AI change governance I guess thatamp;#39;s the big question that weamp;#39;re thinking about I donamp;#39;t know where some of you are from put your hands up if youamp;#39;re from an industry thatamp;#39;s regulated no wonder youamp;#39;re here even even and uh and even industries that are not regulated today you know you have got a lot of privacy policies which are coming out and impacting us all so um this is Iamp;#39;m going through a second data transformation at the moment and um the first one I did a lot of processes and I observed a lot of waste in the organization so I want to talk a little bit about what the problem is that weamp;#39;re tryi

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What Is NPI (Nonpublic Personal Information)? NPI is a subset of PII, as defined in the Gramm-Leach-Bliley Act (GLBA). NPI applies to PII financial institutions collect when performing a financial service on behalf of a customer.
Personally identifiable information (PII) uses data to confirm an individuals identity. Sensitive personally identifiable information can include your full name, Social Security number, drivers license, financial information, and medical records.
Traditional data scrubbing techniques focus on removing or obfuscating PII from datasets. Some common methods include: Data Deletion: Just simply deleting PII data from a dataset. Data Masking: Replacing PII with random characters or symbols to maintain the original data format.
Data Anonymization Techniques Data maskinghiding data with altered values. You can create a mirror version of a database and apply modification techniques such as character shuffling, encryption, and word or character substitution. For example, you can replace a value character with a symbol such as * or x.
How can an agency de-identify data? The key to de-identification is the removal of the identifiers of personal information so that the information is not about an identifiable person. Examples of a direct identifier include, an individuals name, address, telephone number or Tax File Number.
De-identification may also be accomplished by storing the personally identifiable information (PII) of a participant in a separate secure database from other data from the participant. In this case, each participant is assigned an identifier such as a code, algorithm, or pseudonym unrelated to any PII.
For example, de-identification techniques can include any of the following: Masking sensitive data by partially or fully replacing characters with a symbol, such as an asterisk (*) or hash (#). Replacing each instance of sensitive data with a , or surrogate, string.
De-identified patient data is patient information that has had personally identifiable information (PII; e.g. a persons name, email address, or social security number), including protected health information (PHI; e.g. medical history, test results, and insurance information) removed.

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