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  1. Components
  2. Transformations

Data Loss Protection

PreviousMongo AggregationNextData Preparation (Docker)

All component configurations are classified broadly into 3 section

  • ​​

  • Meta Information

Data Loss Protection component in pipeline used to protect or mask the incoming data by using the several techniques so that the loss of important data can be ignored.

Please follow the steps provided in the demonstration to configure the Data Loss Protection component.

Configuring Meta Information of Data Loss Protection

  • Column name: Enter the column name whose data has to be protected.

  • Rule type: Select the rule type to hide the data. There are four types of rules available by which the data can be protected.

    1. Redaction: Redaction is a data masking technique that enables you to mask data by removing or substituting all or part of the field value.

    2. Masking: By selecting this method, the data can be masked by the given character. Once this option is selected, the following value needs to be given:

      • Masking character: Enter the character by which the data will be masked.

      • Characters to ignore: Enter the character which should be ignored while masking the data.

      • Type: Select either Full or Partial for masking the data.

    3. Hashing: Hashing is using a special cryptographic function to transform one set of data into another of fixed length by using a mathematical process. Once this option is selected, then select the Hash type from the drop down to protect the data. There are 3 options available under the Hash type:

      • sha 256

      • sha 384

      • sha 512

    4. Date generalization: For this rule, select a column which is having only date values. There are four(4) options under this rule:

      • Year

      • Month

      • Quarter

      • Week

​Basic Information​
Resource Configuration​
Configuring the Data Loss Protection in a pipeline workflow
Data Loss Protection