Non-identifiers

Non-identifiers are data elements or variables within a dataset that, either alone or in combination, cannot be directly used to pinpoint the specific identity of an individual. These elements lack the necessary specificity to uniquely identify someone. Instead, they serve to provide context, categorize information, or support statistical analysis without compromising individual privacy. Effective anonymization strategies often involve the careful removal or alteration of identifying information and reliance on non-identifiers for data analysis. The primary function of non-identifiers is to make data suitable for public release or internal use without revealing protected health information or other sensitive data. Using these tools properly ensures people's data security.

Non-identifiers meaning with examples

• In a health study, age, gender, and zip code are generally considered non-identifiers because they lack the required specificity to track someone. However, to protect patients' data, additional measures may be necessary. Further steps can include providing information on the patient's age as a range and not an exact date, ensuring anonymity and privacy of the data. This is a way to protect health information.
• Survey responses that are aggregated, such as average income brackets or frequency of product use, are examples of non-identifiers because they do not reveal personal details. However, even when data is aggregated, it is important to protect the privacy of the individual. This is accomplished by protecting data by masking the information that could be easily linked.
• In customer analytics, the number of purchases made in a specific product category, without associating the purchases with a customer's name, becomes non-identifying data. Careful consideration must be taken when managing non-identifiers. Furthermore, the process also has to take into account data privacy regulations like GDPR or CCPA. This is accomplished by ensuring that they can only perform statistical or aggregated analysis.
• Geolocation data at a city level, instead of a specific address, is considered non-identifiable information. It protects the exact location of the individual. Additionally, this data can be used to create maps of general population trends. Non-identifiable data can also be used for analysis and also offers useful, real-time data about what is currently trending.
• Data points such as the type of device used to access a website or the operating system on the device are frequently used as non-identifiers for analyzing user behavior, particularly when aggregated at the population level. When used together, they give us relevant data, which can be further analyzed to improve user experience. This data is valuable to improve user experience, without disclosing personal identifying information.