No Code Platform
DataBuck: Zero-Code Data Validation Platform
No coding required—our intelligent agents autonomously validate and
discover data issues at enterprise scale.
Smarter Detection. Fewer Errors.
80%
Fewer False Positives
Less noise, teams save time
95%
Fewer False NegativesCoverage
Real issues detected early
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Verizon
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Cisco
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Toyota
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ABSA Bank
Traditional DQ Tools → No-Code AI Agents
Why Traditional Data Quality Tools Falls Short
Legacy tools create more problems than they solve with outdated approaches that can't keep pace with modern data environments.
Data engineers spend weeks writing SQL rules and constantly updating them as schemas change. Every new business requirement means more manual coding.
❌ Months of development time
Static rules generate noise while missing context-aware problems. Teams get alert fatigue and critical issues slip through undetected.
❌ 70%+ false positive rate
Complex setup, manual configuration, and integration challenges lead to 6-12 month implementation cycles before seeing value.
❌ 6-12 months to deployment
No-Code Validation Across All Data Quality Issues
DataBuck autonomously discovers and recommends data quality rules focussing on critical data elements that impact on business outcomes.
Observability Checks Auto Recommended
Essential Data Quality Checks Auto Recommended
Anomaly ChecksAuto Recommended
Use Case Specific ChecksGenerated by BuckGPT
Custom ChecksUser Specified - Reusable
All checks are automatically recommended by AI and continuously updated based on your data patterns
Integrates with your data ecosystem
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Databricks
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Snowflake
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BigQuery
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Redshift
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SQL Server
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Oracle
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Postgres
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dbt
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Airflow
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Databricks Workflows
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Azure Data Factory
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Unity Catalog
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Alation
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Collibra
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Trigger remediation via API
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Pull fix results
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Webhook notifications
Enterprise-grade security by design
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• Least-privilege connectors
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• Column-level protections
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• Data masking support
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• Private VPC/VNet deployment
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• Customer-managed keys
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• Network isolation options
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• Audit trails
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• SSO/SAML, SCIM
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• Role-based access controls
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• On Prem
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• Cloud
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• SaaS
DataBuck Validates at Every Stage of Your Pipeline
Continuous quality monitoring from source to consumption
Source Systems
Oracle
SQL Server
Teradata
Ingestion
Informatica
Dbt
Kafka
Data Lakes
Bronze
Silver
Gold
Consumption
PowerBI
Tableau
ML Models
Automated validation at every pipeline stage ensures data quality issues are caught early and resolved before impacting downstream consumers
Frequently Asked Questions
Ready to trust your data?
See DataBuck catch issues on your own tables.