Collibra use case

Data reliability

Overview
Key initiatives
Customer stories
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Monitor, validate and certify the health of your data with automated checks for accurate, consistent and reliable business outcomes

Ensure data quality across multiple sources with automated and targeted rule writing. Remediate faster with no-code, business-ready data quality dimensions and self-service rules for accurate and consistent data products. Visualize data health and certify data for trusted business decisions.

$12.9M

Average annual cost of poor data quality cost to organizations¹

50%

Organizations adopting data quality solutions through 2024²

45%

Those responsible for data who fully trust it³

Key initiatives

Certified and accurate business reporting

Data quality monitoring and detection

Reduce data downtime and code-heavy processes with automated rule writing over AI’s broad and large use of data.

Only Collibra automatically detects anomalies and generates business-ready rules for fast, targeted data remediation.

Data quality validation and testing

Understand the quality of data, easily define what healthy data looks like and see changes that impact your work.

Only Collibra enables the business with clear metrics and self-service rules in natural language for no-code, tailored data quality dimensions.

Data quality reporting and auditing

Understand data health and prioritize columns with greatest impact to improve ROI and compliance.

Only Collibra visualizes data health completely with automated reports for cost, scale, coverage and completeness.

Learn how the Collibra Data Intelligence Platform can help

Get more information on the Collibra Data Intelligence Platform and learn how Collibra Data Quality & Observability automates anomaly detection and rules for more accurate and consistent data.