Data error on the Cloud is elusive and spreads fast Monitor every hop, detect errors early and stop the spread

Leverage AI/ML to execute and scale automatically

Mitigate the risk of incorrect data on the AWS cloud

Would it be useful to detect data errors upstream, so they don't get through to your business partners?

What if you could automate 80% of that work to validate data?

Cloud Data Engineers do not understand every column of every table and find it hard to validate & certify the accuracy of data. As a result, companies end up monitoring less than 5% of their data. The other 95% is unvalidated and highly risky.

DataBuck is a continuous data validation software for catching elusive data errors very early.

Powered by AI and Machine Learning, it easily integrates within your data pipeline through APIs, to discover issues for each data set and validates the reliability and accuracy of data via automation. Cut data maintenance work and cost by over 50% and certify the health of your data quality at every step of data flow automatically.

Benefit of automating data quality validation on AWS

Get drinkable, crystal clear stream of data from AWS along with these benefits…


People productivity
boost >80%


Reduction in unexpected errors: 70%


Cost reduction >50%


Time reduction to onboard data set ~90%


Increase in processing speed >10x


Cloud native

Registration Necessary for Demo and Webinar Attendance.

What DataBuck users say…

Introduction DQ Monitoring on AWS
Autonomous Data Quality validation on Cloud
How AI/ML simplifies Data Quality and increases accuracy

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