Boost Data Trust with AI/ML

Take your data management to the next level by measuring Data Trustability with AI/ML.
Move beyond Data Observability and unlock the true potential of your data.

DataBuck: Empowering Data Quality

DataBuck is the ultimate solution for overcoming data challenges where traditional tools fall short:

  • Cloud/Lake usage
  • Dynamic data (e.g., operational and transactional)
  • High data volumes
  • New data sources or changing structures
  • Unintended data use (data being used for new purposes)

With DataBuck's AI-powered data quality validation, all Systems Risks are automatically detected, setting up numerous checks and thresholds.
Experience its unmatched speed, surpassing other tools by over 10 times.

Customers love the benefits:

    • Enhanced trust in reports, analytics, and models
    • Reduced data maintenance workload and costs
    • 10 times more efficiency in scaling Data Quality operations
People Productivity

People productivity
boost >80%

Reduction in unexpected errors

Reduction in unexpected errors: 70%

Cost reduction

Cost reduction >50%

Time reduction to onboard data set

Time reduction to onboard data set ~90%

Increase in processing speed

Increase in processing speed >10x

Cloud native

Cloud native

4 Classes of Checks for Comprehensive Data Validation

Module 1


DataBuck’s unified Observability platform:

Powered by Machine Learning, DataBuck is an advanced Observability tool that prevents critical data issues before it breaks the data pipeline or reaches the data users.

Module 2


Beyond Observability:
ML-powered Data Trustability

Measure the trustworthiness and usability of data on the cloud, and monitor Data Trustability across the entire data pipeline with the help of DataBuck's Trustability Module.

Module 3

Data Quality

Autonomous Data Quality Validation:

DataBuck is an automated data monitoring and validation software that autonomously validates 1,000’s of data sets in a few clicks, with lower data maintenance work & costs.

Module 4

Data Matching

Cross Platform Data Matching powered by ML:

Reconcile complex data across multiple platforms automatically using no-code Machine Learning to detect errors before they infect multiple systems downstream.

What DataBuck users say…

In The News Popular publications features FirstEigen

Middle Easter Bank and DataBuck

DataBuck customer, Roland Doummar, SVP, Head of Data Gov. First Abu Dhabi Bank, and his team were awarded the Best Use Case of Data Management for 2023 at the Middle East banking AI & Analytics summit #MEBANKINGAI.

Published in

Strategies for Achieving Data Quality in the Cloud

With more and more applications moving to the cloud, the quality of data is becoming a growing concern. Erroneous data can cause all sorts of problems for businesses.

Published in Dataversity

How to Leverage Machine Learning to Identify Data Errors in a Data Lake

A data lake becomes a data swamp in the absence of comprehensive data quality validation and does not offer a clear link to value creation.

Simplify Data Quality Monitoring and Data Quality Validation with DataBuck

Gartner Cool Vendor Award for Data Validation & Data Quality

IDC Innovator Award in
Data Quality

Recognized by Eckerson Group for Data Validation

Recognized by GigaOm for Data Validation

Recognized by CIOReview for Data Quality

Recognized by Intellyx for Data Validation