Projects

The project is the user's workspace. From here you can manage:

• Connections to databases
• Create data lists.
• Manage classification labels.
• Create transformation rules.
• Manage API keys.
• Change your project settings

Databases

In this area you can manage your database connections and your environments. Refer to the databases documentation for more information.

Data lists

You can add project data lists to use in the operations of a rule. You can create two types of data lists:

• TXT: Add a plain text data list by separating the values by commas.
• CSV: You can create a data list by attaching a CSV and selecting the delimiter and if the file contains headers.

These data lists can be used for anonymization and data synthesis operations.

Variables

You can define two types of variables, text or password, which will be encrypted and will only be visible during the variable creation process.

These variables can be invoked from:

• Functions: Any variable defined here can be invoked from any custom function.
• Rules: It is possible to use these variables for Anonymize, Synthesize or, in general, in any text field where Gigantics allows the user to enter a text.

In both cases, the variable will be invoked using:

$(var)

Functions

It is possible to create customized functions to use in data transformations in the model. Like the other configuration items, these functions are available from all the models in the project.

To learn more about how to create a function, see Custom Functions.

Labels

Labels are used to categorize the fields analyzed during the Discover step within a Model.

Gigantics provides a set of labels (internal), however, the user can enable/disable them individually as well as create new ones (custom/ labels).

Custom labels

To create a new label (custom) and that can be used in any project model, it is necessary to indicate or give a hint so that gigantics can assign the label to a field.

In the type field, you specify what type of help or hint is offered:

• Metadata hint: Matches the entity or the field name to apply the label.
• Data Matchers: Matches the record value to apply the label.

You can define the label as PII Data and assign it a severity that will be displayed in the discover stage of any model in the project.

In the Masking, it is possible to assign a transformation function to the label. This function has to be defined in the Functions section.

So, for example, we want to create a 'user/gender' tag that is also sensitive data and applies only to certain entities that match a regular expression:

Name: user/gender
Type: Metadata hint
 
Entity (regex): ^employ.*
Field (of the entities that match the regex) (regex): ^gender
 
Entity (text): customers
Field (text): gender

In the case of using the Data Matcher type, the application will go through all the values and assign the label to those fields:

Name: user/gender
Type: Data Matcher
 
Include (regex): ^(M|F)$
Include (text): M

With this configuration, Gigantc will assign the user/gender label to all fields which contain the value M or M or F.

API

In Gigantics, API keys are used to invoke datasets, pipelines, and jobs from external systems (CI/CD, scripts, etc.).
Below is the updated flow:

Creating an API Key

1. Go to the project section.
2. Click Create API key and enter a purpose/description to identify it.
3. The key and the base URL will be displayed. Copy the key and store it in a safe place (it will not be shown again).
4. In the key list you will see the purpose, part of the identifier, date/time, and the number of invocations.
   From there you can revoke, edit, or delete the key.

Authentication

Every request to the API must include the key using one of these methods:

• HTTP header

  Authorization: Bearer <API_KEY>

• URL parameter

  <GIGANTICS_ENDPOINT>?api_key=<API_KEY>

Examples with curl

Header

curl -X POST "<GIGANTICS_PIPELINE_ENDPOINT>" \
     -H "Authorization: Bearer <API_KEY>"

URL parameter

curl -X POST "<GIGANTICS_PIPELINE_ENDPOINT>?api_key=<API_KEY>"

Store the key in an environment variable or in your CI/CD platform’s secret manager to avoid exposing it.

Endpoints

The full URLs (including organization, project, model, and resource) are shown in the Gigantics interface when you assign the API key.
All you need is the API key and the provided URL.

Response when running a pipeline

When a pipeline starts, Gigantics responds with:

{
  "job_id": "64c8c45b8a5f1e001a3db9aa",
  "job_url": "https://<host>/api/job/64c8c45b8a5f1e001a3db9aa"
}

• job_id: Internal identifier of the job.
• job_url: URL to check its status.
  Once the job finishes (status = completed) and the pipeline generates a dataset, the link to the resulting dataset will appear at this same URL.