> For the complete documentation index, see [llms.txt](https://cortex-docs.paloaltonetworks.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cortex-docs.paloaltonetworks.com/data-security-documentation/data-security/cortex-data-security-terminology.md).

# Cortex Data Security terminology

The following is a list of the basic terms related to Cortex Data Security:

* **Data asset:** Any asset that contains data in a customer environment.
* **Storage:** A data asset that contains folders and files.
* **Database:** A data asset that contains structured data in tables and columns. It can also contain semi-structured data (non-tabular data).
* **Disk:** A type of data asset that is a VM disk in cloud environments such as EBS for AWS, managed disks in Microsoft Azure, and Persistent Disk in Google Cloud Platform (GCP). These can host files, folders, and databases.
* **Discovery:** The process of detecting data assets in a customer environment.
* **Data classification:** The process of scanning data for sensitive records and identifying the class and quantity of sensitive records within a data asset.
* **Object:** An instance of either files or columns, in a storage asset or database asset, respectively.
* **Data pattern:** The basic structure of data that is discovered in an object, such as an email address, an IP address, a phone number, a name, a credit card number, and a bank account number.
* **Data profile:** A group or category of multiple data patterns sharing similar attributes. For example, personally identifiable information (PII) is a data profile that could include an email address, phone number, or name. Another example of a data profile is developer secrets, which might include a token, AWS key, or certificate.
* **Sensitive Record:** A sensitive record is defined by having a data pattern that is matched with a data object.
* **Collabration**: Connects to collaboration and business applications such as Microsoft Teams, SharePoint, OneDrive, Google Workspace, and Salesforce to discover and protect sensitive data across files, messages, and business records.
* **False positive:** A case where certain data is detected as being a specific data pattern but actually matches a different data pattern or possibly should not match any data pattern at all.
* **Data security finding:** Findings are security-related insights that are generated as part of data scanning but are not necessarily actionable. For example, "shadow backups found” is an example of a finding that can be generated by the Cortex Data Security scanner.
* **Data security issues:** Issues reflect actionable security risks that are generated by a Data Policy. For example, “sensitive public object in private asset” is an issue referencing a scenario where an object is publicly accessible while the asset configuration does not make it entirely public.


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