digna Data Schema Tracker

digna Data Schema Tracker

digna Data Schema Tracker

Stop schema drift before it breaks your pipelines

digna Data Schema Tracker continuously monitors your database structure, alerting you to added/removed columns, data type changes, and other modifications—whether intentional or accidental.

By alerting you early, it prevents silent schema drift and minimizes the risk of downstream issues, such as broken pipelines. 

By alerting you early, it prevents silent schema drift and minimizes the risk of downstream issues, such as broken pipelines. 

By alerting you early, it prevents silent schema drift and minimizes the risk of downstream issues, such as broken pipelines. 

How digna Data Schema Tracker Works

Tracks structural changes across your tables, including added or removed columns, renamed fields, and data type changes.

Simply enable tracking on your tables - digna inspects the structure on each scan and flags any deviation from the previous version.

Every schema change is timestamped, attributed, and stored. This makes it easy to trace what has changed and when - essential for auditability in regulated environments.

Ready to get started?

Ready to get started?

Ready to get started?

Use Case: Customer Profiles Schema Changes

Detect and act on structural modifications:

Data Source

Table Name

Change Type

Field Affected

Change detected on

Current Data Type

Previous Data Type

crm_platform

customer_profiles

Column Added

loyalty_status

2025-06-01 12:33:00

CHAR(1)

-

crm_platform

customer_profiles

Data Type Changed

signup_date

2025-06-20 00:00:10

String

DATE

crm_platform

customer_profiles

Column Removed

is_subscribed

2025-07-02 16:33:00


BOOLEAN

Outcome: digna flags the removal of is_subscribed (used in 12 downstream reports) and the risky DATE → STRING conversion for signup_date.

Use Cases

Data Platform Stability

✦ Detect breaking changes before pipelines or dashboards fail

✦ Spot unintended schema edits from upstream contributors

✦ Prevent “invisible errors” that cause data type mismatches

Data Platform Stability

✦ Detect breaking changes before pipelines or dashboards fail

✦ Spot unintended schema edits from upstream contributors

✦ Prevent “invisible errors” that cause data type mismatches

Data Platform Stability

✦ Detect breaking changes before pipelines or dashboards fail

✦ Spot unintended schema edits from upstream contributors

✦ Prevent “invisible errors” that cause data type mismatches

Key Benefits of

DATA SCHEMA TRACKER

Eliminate silent schema drift across environments

Minimize the risk of pipeline failures and BI tool errors

Maintain schema stability in shared data contracts

Supports Snowflake, Databricks, BigQuery, etc

Eliminate silent schema drift across environments

Minimize the risk of pipeline failures and BI tool errors

Maintain schema stability in shared data contracts

Supports Snowflake, Databricks, BigQuery, etc

Eliminate silent schema drift across environments

Minimize the risk of pipeline failures and BI tool errors

Maintain schema stability in shared data contracts

Supports Snowflake, Databricks, BigQuery, etc

Key Benefits of

DATA SCHEMA TRACKER

Prevent breakages. Maintain trust. Monitor your schema with digna.

Prevent breakages. Maintain trust. Monitor your schema with digna.

Prevent breakages. Maintain trust. Monitor your schema with digna.

FAQs

Can I track schema changes automatically in my data warehouse?

Can I track schema changes automatically in my data warehouse?

Can I track schema changes automatically in my data warehouse?

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