Ensure better data quality by monitoring data SLAs, unexpected column changes, and null records before they get to your consumers.
Databand detects bad data quality while it’s in motion so that you can guarantee confidence across your data teams.
Catch data schema and data profiling anomalies, such as null counts, type changes, and skews.
Make sure high-quality data is delivered on time and successfully.
Prevent data failures before they reach your downstream consumers and production tables.
Understand the data quality health of your datasets while keeping context that shows you what pipelines interact with those critical assets.
Databand automatically captures your dataset trends, so you notice which patterns in bad data quality need attention.
Databand helps uncover unknown data quality problems by capturing the metadata from your datasets and alerting you when dataset operations change unexpectedly.
Identify problematic datasets related to schema changes and column-level statistics.
