A branch location specifies a site where the file servers, databases, and data centers that contain data to scan are located. Branch locations are used to indicate where different data stores are physically located. For more information see Managing Branch Locations.
A sensitivity level defines how sensitive the data is. Sensitivity levels are required in creating classification profiles and data stores. For more information see Sensitivity Levels below.
An information type (or infotype) categorizes data to look for during a scan. A large number of predefined information types are available to better categorize the data. For more information see Information Types.
A tag helps group data together. Tags are used to filter data for generating reports. They can be specified when creating data stores and classification profiles.
Data Discovery and Classification includes a number of predefined Tags, but also provides the ability to create custom Tags when creating data stores and classification profiles.
The predefined Tags are APA, APPI, CCPA, FINANCIAL, GDPR, GDPR-FINANCIAL, GDPR-HEALTHCARE, GDPR-ID, GDPR-PII, HEALTH, HIPAA, KVKK, LEGAL, LGPD, NYDFS, PCI, PERSONAL, PHI, PII, SHIELD and UK-GDPR.
A classification profile defines what kind of sensitive information to search for during a scan. It includes information such as a sensitivity level, information types, and tags. Classification profiles can be created based on predefined templates or custom templates. For more information see Managing Classification Profiles.
A file, a database table, and a BLOB in a database table as stored in a data store are called Data Objects.
Sensitive Data Object
A data object that contains any data match is called a Sensitive Data Object.
A concrete instance of any of the infotypes is called a Data Match.
A risk is the presence of a sensitive data object in a data store.The risk is calculated per the data object and data store. The risk is directly related with the matches found in the data object or data store.
A scan is an entity that helps in scanning data stores. Each scan specifies the location to scan and what to look for during scanning. Findings of scans can be used to generate reports for different purposes. Scans can be either run manually (any time) or scheduled to run and stop at a specified time. For more information Managing Scans.
A sensitivity level defines how sensitive the data is. Sensitivity levels are required in creating classification profiles and data stores. Prebuilt sensitivity levels are:
None: The sensitivity level for such data has not yet been specified.
Public: Specifies the least sensitive data with no specific need for data security. Such data can be shared with anybody.
Internal: Specifies the data with low sensitivity. Exposure of such data may not affect an organization, but is not meant for public disclosure.
Private: Specifies that the data is personal. Such data should be protected from public viewing.
Restricted: Specifies highly sensitive data, for example, customer's personal data and trade secrets etc. This type of data requires the best possible data security. Disclosure of such data can lead to severe financial and legal consequences for an organization. Businesses must prioritize remediation efforts related to this type of data.
DDC uses AES256 encryption to protect sensitive data. For that purpose, DDC creates a number of encryption keys that are stored in CM. You can find these DDC keys in the Keys & Access Management application in CM:
Four encryption keys to protect the Hadoop configuration before storing it inside the DDC Database. Each key is used to protect one configuration parameter (PQS Server, PQS credentials, HDFS Server, and HDFS credentials). These keys have the following format: citrus-
UUID(for example, citrus-6e0cb668-3a3d-4f2c-8687-17092b83b41b).
As many encryption keys as there are data stores, and each key is used to encrypt the data store credentials before storing them inside the DDC Database, and to encrypt the results of the scans completed in that data store, before storing them in HDFS. These keys have the following format: d
UUID(for example, d8b2d8404-c9ae-4a34-800a-01258dfaa383).
As many encryption keys as there are scans, and each key is used to encrypt the scan data before storing it in HDFS. These keys have the following format: s
UUID(for example, s14912791-bed5-4e73-b733-6a36ecfe338f).
These keys must never be deleted, or DDC will not be able to process the related scans or data stores properly.