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2024.2
  • Immuta Documentation - 2024.2
  • What is Immuta?
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      • Starburst (Trino) Integration Reference Guide
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        • Data Source Health Checks Reference Guide
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          • Schema Monitoring
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        • Why Use Schema Monitoring?
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      • Built-in Classification Frameworks Reference Guide
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        • User Identity Best Practices
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      • Detect Monitors Reference Guide
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    • Getting Started with Secure
      • Automate Data Access Control Decisions
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        • Managing User Metadata
        • Managing Data Metadata
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        • Managing User Metadata
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    • Introduction
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          • Author a Subscription Policy
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          • Author a Masking Data Policy
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      • Domains Reference Guide
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        • Why Use Purposes?
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        • Enable Masked Joins
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  • Releases
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    • The Immuta CLI
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            • Write Policies Payloads and Response Schema Reference Guide
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        • Subscribe to and Manage Data Sources
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          • Manage Projects
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On this page
  • Anti-patterns: Using Immuta without schema monitoring
  • Business value
  • What features does it pair with?

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  1. Data and Integrations
  2. Registering Metadata
  3. Schema Monitoring

Why Use Schema Monitoring?

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Last updated 9 months ago

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Immuta is a live metadata aggregator - metadata about your data and your users. With data metadata specifically, Immuta can monitor changes in your database and reflect those changes in your Immuta tenant through .

When schema monitoring is enabled, Immuta monitors your organization's servers to identify when new tables or columns are created or deleted, and automatically registers (or disables) those tables in Immuta. The newly updated data sources then have global policies and tags applied to them, and the Immuta data dictionary is updated with column changes.

Schema monitoring keeps Immuta in sync with your data environment, helping you remain compliant without having to manually update individual data sources.

Anti-patterns: Using Immuta without schema monitoring

Without schema monitoring, data owners have to manually add and remove Immuta data sources when users add or remove tables from databases in their data platforms. At worst, data owners are not aware of these changes; at best they are aware of the changes and have to manually update Immuta with those changes, which is a time-consuming, error-prone process.

Beyond draining data owners' time, manually updating data sources to reflect the state of the data platform also complicates the process: not only must they understand when a new table is present, but they then must remember to tag it and protect it appropriately. This leaves organizations ripe for data leaks as new data is created across the business, perhaps daily.

Schema monitoring, by contrast, is scalable and accounts for the evolution of your schemas and policies. Instead of manually managing access to these tables or adding and removing data sources, you are empowered to register a schema, create policies, and allow Immuta to manage those policies and changes to your schema for you to keep your data in sync and restrict access appropriately.

Business value

Both monitoring for new data and align with the , removing redundant and arduous work. Once tables are registered and tagged, policies can immediately be applied - this means humans can be completely removed from the process by creating tag-based policies that dynamically apply themselves to new tables.

Then, your business reaps the following benefits:

  • Increased revenue: Accelerate data access and time-to-data access because where sensitive data lives is well understood.

  • Decreased cost: Operate efficiently and move with agility at scale.

  • Decreased risk: Discover and protect sensitive data immediately.

What features does it pair with?

Schema monitoring pairs with the following features:

: Column detection identifies when a column has been added to or removed from a table and adds or removes that column from the data source in Immuta.

: When paired with column detection or schema monitoring, this policy locks down access to those newly added columns and tables to prevent data leaks.

: When the tables are discovered through the registration process, Immuta evaluates the table data for sensitive information and tags it as such. These tags are critical for scaling tag-based policies.

: Global data and subscription policies can be created using tags so that they immediately enforce appropriate access restrictions on tables and columns when they are added.

schema monitoring
discovering and tagging sensitive data
concepts of scalability and evolvability
Sensitive data discovery
Global data and subscription policies
Column detection
New column added templated global policy