Avoid Production Defects with Better Data Pipeline Observability
With the growing complexity of data systems, data pipeline observability is very time-consuming and nearly impossible to achieve. Worse still, without this deep understanding of data pipeline and agile development requirements, every change to the environment carries a high risk of broken releases. To deal with this complexity, data teams allocate up to 40% of their resources to carry out manual impact analyses. MANTA cuts down on manual effort by enabling agile change management with fully-automated impact analysis, incident resolution, and debugging.
Key Benefits
Save Time, Money, and Resources
Increase the productivity of your data team by 30–40% with better visibility of your data pipeline thanks to fully-automated impact and root-cause analyses that require no or minimal manual labor
Perform Incident Resolution 90% Faster
Easily trace any data-related issue back to the source to remove it right away and prevent it from happening again in the future
Reduce the Number of Broken Releases to Less Than 1%
Act proactively with automated and accurate impact analysis that gives you immediate visibility of how a planned change will influence other parts of the environment

Gartner® Market Guide for Active Metadata Management
According to July 2021 Gartner® Market Guide for Active Metadata Management report, we’re a Representative Vendor. Download a copy to learn why.
Automated Data Lineage: The Cornerstone of Effective DataOps
Learn how DataOps can use automated data lineage to solve inefficiencies, speed up data analytics delivery, and close the gap between technical and business users for effective collaboration across your data pipeline.
Enabling DataOps in a Large DWH with Automated Lineage for Shorter, Bug-Free Releases
Read how MANTA helped a customer facilitate frequent changes, releases, and continuous deployment in a large environment of over 1,000,000 algorithms.

MANTA Revisions Feature: Overview
Read how MANTA’s time slicing feature allows you to see and compare past data flows to identify what has changed in the flow and help you implement DataOps.
Who Do We Help?
Data Engineers
- Immediately test even the smallest changes for a risk-free deployment
- Fast and painless incident resolution
- Get full visibility of data pipelines for further optimization and improvements
Data Analysts
- Enable IT and business collaboration with a full understanding of the impacts of planned changes
- Questions about critical reports and data origins are answered in a few clicks
Data Scientists
- Fully understand data provenance for better AI/ML
- Faster and more efficient data preparation
- Visibility of designed algorithms is improved with lineage