How ITSV Eliminated 9,000 Data Quality Rules with AI-Driven Observability

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INDUSTRY

Healthcare, Social Insurance

INDUSTRY

Healthcare, Social Insurance

INDUSTRY

Healthcare, Social Insurance

USE CASES

Data Quality Monitoring, Timeliness Assurance

USE CASES

Data Quality Monitoring, Timeliness Assurance

USE CASES

Data Quality Monitoring, Timeliness Assurance

MODULES USED

digna Data Anomalies, digna Data Timeliness

MODULES USED

digna Data Anomalies, digna Data Timeliness

MODULES USED

digna Data Anomalies, digna Data Timeliness

The Challenge: 9000 Rules. No Control.

Before implementing digna, ITSV — the IT backbone of Austria’s social insurance — was managing data quality through 9000 hand-crafted rules in its data warehouse. But this traditional approach wasn’t keeping up with the pace or complexity of modern data:

Only 25% of relevant data quality cases were actually covered

In short: data quality was out of control, and trust in the system was at risk.

The Solution: AI-Powered Anomaly & Timeliness Monitoring

As early as September 2021, we started the Proof of Value with ITSV and began replacing its entire rule-based framework with digna Data Anomalies and digna Data Timeliness — making a full shift to AI-driven observability and trust.

Only 25% of relevant data quality cases were actually covered

Use Case: Nationwide Social Insurance Data

ITSV's warehouse integrates data from five health insurance providers, serving millions of Austrians. This includes highly heterogeneous, sensitive datasets used in billing, medical claims, patient insights, and more.

The challenge wasn’t just data quality — it was data volume, velocity, and accountability. digna made it possible to:

✦ Monitor all incoming tables without writing or rewriting a single rule
✦ Ensure data freshness across regions and pipelines — even without defined schedules
✦ Provide self-service anomaly detection across teams — boosting adoption and coverage

The Results: From Chaos to Confidence

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

✦ 86% alert volume — only the most meaningful issues are surfaced

✦ +260% increase in case coverage — with no added maintenance

✦ Teams can now focus on insights, not infrastructure

✦ By December 2022, ITSV decided to implement digna as a No. 1 data quality platform for the entire Austrian social security organization, extending beyond ITSV's data warehouse.