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Detect all errors

Prevent bad data from sneaking into your business

Combine explicit tests for business rules with self-learning monitors that detect anomalies without fragile thresholds. All set in minutes.

Volume
transactions
Unexpeced level shift detected: Expected 44,750,000 but value shifted to 44,950,000.

Impact:
Customer Report
Monthly Revenue Report
Tue 23Thu 25Sat 27Mon 2944,600,00044,800,00045,000,00045,200,000

Unified error detection

Tests and monitors working hand-in-hand

Combine automated testing and self-learning anomaly monitoring into one powerful data testing strategy to detect all errors.

Business logic tests

Bring your existing dbt tests into Synq and gain an up-to-date overview of data quality across your stack.
  • Assess values and shape of your data
  • Highlight broken data contracts
  • Keep your data aligned with your business rules

Adaptive monitors

Complement business rules with self-adapting monitors that learn how your business works.
  • Detect data pipelines that stop running
  • Act on sudden drops or increases in your data
  • Discover trends that might become issues

No manual thresholds

Monitors that learn how your business works

Automatically adapting to seasonality of your business, learning from your feeedback, with explainable predictions. Our multi-stage monitoring pipeline accurately detects anomalies while reducing false positive alerts.

Robust seasonal models

Deploy monitors that learn your business' trends and weekly and intraday seasonalities.

Adapting to your feedback

Prevent alert fatigue by controlling how Synq monitors work. Synq learns from your feedback and adjusts its sensitivity to your risk profile.

Explainable predictions

Is it a one-off spike or a long-term shift in your data? Go beyond finding an anomaly. We help you understand what exactly happened.

Strategic placement

Detect errors early with precisely placed monitors. Keep your inbox clean.

Prevent alert overload by deploying monitors where they provide the most value. No need to blast anomaly detectors everywhere to detect the same issue.

source.usage
source.charges
source.coupons
usage
charges
revenue
support
monthly_revenue
performance
usage
stripe.charges
stripe.coupons
source.charges

Unexpeced level shift detected: Expected 44,750,000 but value shifted to 44,450,000.
5 downstream assets impacted:
charges
revenue
support
monthly_revenue
performance

Handpick tables to monitor

Select any subset of tables in your data warehouse to monitor exactly what you need.

Automate placement with dbt

Select tables related to dbt sources or with relevant metadata to control where monitors deploy.

Route alerts to the relevant people

Surface anomalies in alerts targeted to the right people to prevent alert overload.

Comprehensive monitoring

The right monitors for every use case

Volume monitor

Identify abnormal changes in volumes of your data. No more, and no less than expected.

Freshness monitor

Detect changes in the refresh rate of your data.

Distribution

Surface sudden changes in data distributions.

Schema

Catch schema changes that break downstream pipelines.

Important data alerts left unnoticed in the Slack noise?

Define ownership across your data tests and monitors and bring relevant and targeted alerts directly to the right people. Activate ownership

Stop the bad data with Synq

Join data-forward companies in practively preventing data issues.

Trusted by data-forward businesses.

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