Sifflet

Founded by Salma Bakouk in 2021

Detect data pipeline issues, track end-to-end lineage, and resolve root causes across data stacks

Pricing model

Demo, Paid

Rating

★ Positive

Time to value

> 1 Hour

You can use Sifflet to track data quality and fix pipeline errors before they affect business decisions. The system maps complete lineage from data sources to dashboards, letting you see upstream origins and downstream dependencies for every metric. It monitors tables and metrics automatically, detecting unexpected anomalies and schema changes across your warehouses and transformation workflows. When alerts trigger, team members receive root-cause context to diagnose incidents quickly, maintain SLAs, and document datasets in a centralized catalog.

What Sifflet does

Map data lineage across cloud databases and reporting toolsSet automated monitors for table freshness and data completenessDetect schema drift across warehouse tables in real timeIngest dbt tests to establish dynamic threshold alertsInvestigate root causes of pipeline failuresCatalog datasets and document table ownership across teamsTrack data SLA compliance across critical business tablesEnd-to-end field-level data lineage tracking across pipelines and BI dashboardsAutomated anomaly detection for schema drift, volume shifts, and freshness delaysIntegrated searchable data catalog with automated documentationDirect ingestion of dbt test results with dynamic threshold alertsRoot-cause analysis workflows linking upstream code changes to downstream impactsNo-code join configuration for cross-table data consistency checksConfigurable alerts and incident routing to prevent SLA breaches

Pricing breakdown

Pricing model: Book a demo

Frequently asked

Snowflake

Databricks dbt

dbt

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