Data export service

You can leverage the Gatekeeper Data Export service to extract raw data and build the copy of the entire Gatekeeper fields into an in-house database. This can be achieved by leveraging a standard ETL tool, such as Azure Data Factory, or others equivalents.

How to build the ETL pipeline

Export data

Gatekeeper offers a mechanism to export baseline data for typical ETL process. Click here to get the data schema and the documentation of each attribute.

The entire schema is offered as a set of CSV files representing the following:

Entity attributes

Following are the entity schema files. The entity schema files have the ent- prefix added to their name:

  • ent-engagements
  • ent-fraudsters
  • ent-groups-persons
  • ent-groups
  • ent-media-segments
  • ent-persons
  • ent-processed-audio
  • ent-sessions
  • ent-voiceprints-enrollment-segments
  • ent-voiceprints
  • ent-watchlists-fraudsters
  • ent-watchlists

Operation attributes

Following are the operation schema files. The operation files have the opr- prefix added to their name:

  • opr-delete-personal-data

Factor result attributes

Following are the factor results files. The result files have the res- prefix added to their name:

  • res-channel-playback-detections
  • res-detect_known-fraudsters-voiceprint
  • res-detect-known-fraudsters-convoprint-details
  • res-detect-known-fraudsters-voiceprint-details
  • res-enroll-convoprint
  • res-enroll-voiceprint
  • res-identify-convoprint-details
  • res-identify-convoprint
  • res-identify-voiceprint-details
  • res-identify-voiceprint
  • res-lock-convoprint
  • res-lock-voiceprint
  • res-opt-person-in
  • res-opt-person-out
  • res-process-audio-for-enroll
  • res-process-audio
  • res-process-text
  • res-record-media
  • res-sessions-factors
  • res-sessions-involved-fraudsters
  • res-sessions-involved-persons
  • res-suspicious-session
  • res-synthetic-speech-detection
  • res-train-voiceprint
  • res-unlock-convoprint
  • res-unlock-voiceprint
  • res-validate-text
  • res-verify-convoprint
  • res-verify-voiceprint

Nuance recommends using the schema CSV files as a starting point to build an SQL relational database where each CSV represents a separate table, and each table can be linked using foreign keys. For example, they can link the factors to gk_session_id and gk_engagement_id.

Schema headers

Each schema CSV file comes with headers, as mentioned below, so that customers can monitor possible changes to the schema:

  • a versioned number
  • a schema name (also known as <dataset-name>)
  • a schema description
  • a creation timestamp

The addition of new fields is not considered a breaking compatibility point.

General description of the schema columns

Generally the name of the schema file represent the name of a table in the destination SQL Database.

The following table describes fields mentioned in schema CSV files:

Fields of the schema CSV files
Field Description
NAME Field name
DISPLAY_NAME Friendly field name
DESCRIPTION Verbal field description
TYPE Field type (for the column creation in the database)
ENUM_VALUES Possible value of the enumerator
VALUE_EXAMPLE Representative example of the value
IS_MANDATORY If the field is mandatory
IS_DEPRECATED If the field was deprecated
ADDED_IN_VERSION Schema version when a specific attribute was added
MODIFIED_IN_VERSION Schema version when a specific attribute was modified

Download the data schema file

Download the latest data schema file from the following link:

Export data output

Gatekeeper generates a zip output file that contains all the aggregated CSVs. The zip is generated every 5 minutes.

You can access that zip through an https URL pattern. For example, https://<Gatekeeper public API endpoint>/v1/data/gk_scope_id/<schema-name>/yyyy/MM/dd/HH/<schema-name>-yyyyMMddHHmm-yyyyMMddHHmm.zip.

The following tables lists more detailed examples:

Data output examples
Example Example description
https://gatekeeper.api.nuance.com/v1/data/86ebb5d4-a431-4c21-8131-0880f17709fa/ent-engagements/2022/10/15/14/ent-engagements-202210151405-202210151410.zip This example describes a five minute chunk of raw data between 14:05 and 14:10 UTC exclusive.
https://gatekeeper.api.nuance.com/v1/data/86ebb5d4-a431-4c21-8131-0880f17709fa/ent-engagements/2022/10/15/14/ent-engagements-202210151410-202210151415.zip This example describes the five minute chunk of raw data between 14:10 and 14:15 UTC exclusive.

HTTP response status codes

HTTP response status codes indicate if a specific HTTP request has been successfully completed. The x-ms-error-code header is available in case of error only. Following are common response codes and x-ms-error-code header value during client error:

Details on HTTP response status codes
Scenario HTTP status code x-ms-error-code header value
API passed successfully 200 (OK) -
Argument validation check failed 400 (Bad Request) InvalidArgument
Authentication check failed 401 (Unauthorized) -
Authorization check failed 403 (Forbidden) AuthorizationFailed
Requested zip file is in progress 404 (Not Found) FileInProgress
Requested zip file doesn’t exist 404 (Not Found) FileNotFound
Internal error occurred 500 (Internal Server Error) InternalServerError

For more details on HTTP status codes, see HTTP response status codes  .

General description of output columns

Each CSV output file has its own columns that are documented in the schema CSV. There are three special columns:

  • $field_mask: List of fields used in the request - mainly important of an updated record, to determine which fields were updated among all other columns.
  • $operation: An enum that describes which operation is performed:
    • 1 is for insert.
    • 2 is for update.
    • 3 is for delete.
  • $timestamp: Original timestamp of the time when an event is published in Gatekeeper. Note that this timestamp is different from the timestamps visible in the web portal.
  • $internal_reference_id: Contains information about the ID that helps in debugging what went wrong with the record.

Scope configuration parameters

The following are the configuration parameters to control export data: