Automatic data monitoring for modern data teams.
Analytics and data engineering teams use Bigeye to keep data fresh, high quality, and trustworthy.
Bigeye helps SignalFire monitor the millions of data points we crunch for our investment team and portfolio, ensuring all the datasets are fresh, accurate, and complete.
Build trust in every dataset
Every time your users report a data quality outage, they trust the data less. Bigeye helps you rebuild trust, starting with monitoring.
Analytics
Broken dashboards
Find missing and busted reporting data before executives see it in a dashboard.
Machine learning
Damaged models
Get warned about issues in training data before models get retrained on it.
Data culture
Data driven depression
Fix that uncomfortable feeling that most of the data is mostly right, most of the time.
Monitor the data. Not the pipeline.
Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data.
- Freshness
- Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestators go down.
- Volume
- Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected.
- Formats
- Validate values in string columns to ensure UUIDs, ZIP codes, lat/lng are logged as expected.
- Categories
- Find out about changes to event names, region codes, product types, and other categorical data.
- Outliers
- Warnings about test values, math mistakes, even broken sensor results helps you prevent impact to rollups and aggregates.
- Distributions
- Detect and dig in to sudden shifts in summary statisitics that might raise questions or mess with models.
Designed for data people.
By data people.
We built tools for managing petabyte scale data platforms. Now we're building them for you. Our team →
- for analysts
- Discover data issues before your users do
- for data engineers
- Easily integrate into any data stack
Add monitoring and alerting to your datasets in minutes and be the first to know about any data issue before it impacts your users.
AutometricsAlgorithmically generated data quality metrics help you add monitoring to any table in seconds.
AutothresholdsForecasting-based alert thresholds learn each data quality metric and adjust themselves continuously.
CustomizationManual adjustment options for any metric or threshold, and a templating system for defining new metrics.
No-code interfaceA fast and intuitive interface makes it easy to investigate alerts and root cause issues quickly.
Stand up self service data quality monitoring that the whole team can use and connect it to your infrastructure with extensive APIs.
DatabasesConnect to Snowflake, Redshift, BigQuery, and other popular OLAP and OLTP sources.
APIsFull parity with the no-code UI allows for creating, editing, and reading configuration or metric history.
SaaSConnect to data and monitor in minutes with a managed service that never copies your raw data.
Private cloudEasily up inside your VPC with infrastructure templating like Cloudformation for AWS.
Reliable data doesn't have to be hard.
Bigeye helps data teams detect and fix data quality problems together.