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Introduction to Delphix Compliance Services (DCS)

Delphix Compliance Services (DCS) offers a robust and reliable solution for masking sensitive data by simplifying the masking process within a secure, customizable, and efficient system. This page provides an overview of the fundamental aspects of DCS and outlines the basic steps to start using this tool.


DCS supports in-place masking, where the original data source also serves as the masking target. This ensures a streamlined and efficient masking process.

Masking data

Masking data with DCS involves three primary steps:

  1. Connect to data securely
    DCS establishes a secure connection to a data source, like a staging dataset or application sandbox, through OAuth or direct username and password authentication.

  2. Select masking rules
    Customize your data masking approach by selecting from a range of predefined or custom algorithms, along with a pre-set ruleset, to address complex data sets effectively.

  3. Start a compliance job
    With a connection and ruleset in place, execute a compliance job. This process involves a connector, the chosen ruleset, and optional parameters. The job’s progress can be monitored in real time.

Initial capabilities and expansion

Originally, DCS was designed to mask data exclusively from Salesforce. However, it has expanded its capabilities to include data from Azure sources.

Suggested prerequisites

Please note that there are specific requirements for Salesforce and Azure, respectively. Ensure the user connected to DCS has adequate read and write privileges and that there is sufficient API capacity for the compliance and synchronization jobs.

Key terms in DCS

Understanding these terms will help you navigate the DCS environment more effectively:

  • Connector: Acts as a bridge between DCS and a data source, facilitating data fetching and masking.

  • Domain: Classifies data into logical groups (e.g., “address”, “SSN”) for more efficient masking.

  • Algorithm: The set of rules defining how data is masked.

  • Ruleset: Dictates how columns in a data source are masked, mapping them to specific algorithms.

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