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Monitor your data assets, metadata, and infrastructure all in one place

Don't sleep on bad data

Comprehensive data and metadata monitoring

Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics.

Comprehensive data and metadata monitoring
Get to the root cause & assess the impact

Full data stack lineage
with column-level detail

Exhaustive mapping of all dependencies between assets, from ingestion to BI.

Data lineage with column-level detail
Break data silos

Enhanced productivity and collaboration between data engineers and data consumers

Information-rich data catalog
Root cause analysis
Incident management reporting.

Information-rich data catalog
From data ingestion to consumption

Get a bird's eye view of your entire data stack

Sifflet seamlessly integrates into your data sources and preferred tools, and can run on AWS, Google Cloud Platform, and Microsoft Azure.

Image of square shapes with technology platform logos, such as DBT, Databricks, Google BigQuery,  Snowflake, Amazon Redshift, Tableau, Looker, PostgreSQL, Hive, etc.

Customer
Stories

Sifflet ticked all of our boxes

"In addition to monitoring the quality and accuracy of the data assets, we were also looking to ensure the reliability of the pipelines, observe schema changes and other metadata-related metrics. More than anything else, we wanted to know the root cause of each anomaly detected and conduct proper incident management reporting. Sifflet ticked all of our boxes."

Logo Meero
Laurent Tachet des Combes
Head of Data, Meero
CUSTOMER STORIES

Sifflet ticked all of our boxes

In addition to monitoring the quality and accuracy of the data assets, we were also looking to ensure the reliability of the pipelines, observe schema changes and other metadata-related metrics.

Laurent Tachet des Combes
Head of Data, Meero
Read the customer story →

With Sifflet we know what to do once the rule fails

We chose Sifflet for its wide offering. We’ve checked out other vendors from the space, and they have all data quality rules, but what we need is the next step. Being able to know what to do once that rule fails.

Ross Serven
Director of Data Engineering, Nextbite
Read the customer story →

Sifflet allows you to find and trust your data

It is very convenient to have the data quality feature together with the data catalog. I think it’s a great combination: the data catalog allows you to find all the data you need and the data quality feature monitors our data flows, ensuring that the data we use is reliable at all times.

Marco Kleine-Böhme
VP Data & Analytics, jobvalley

FAQs

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