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Provide clarity on data origin, transformations, and usage across your landscape.
Our Column-Level Lineage mapping offers deep visibility into your data pipelines, enabling you to trace issues down to the most granular level. By pinpointing the exact origin of data discrepancies and understanding their downstream impact, you can resolve problems faster and more effectively. This level of insight ensures timely resolution and minimizes disruptions across your data workflows.
Easily define and manage data lineages manually wherever automated tracking may fall short. With Decube, you can establish an approval workflow for data owners, ensuring that every manually defined lineage is accurate and aligned with organizational data governance standards. This flexible approach helps maintain data integrity and fills in gaps for complex or custom data assets.
When changes occur within a data asset—such as a table, job, or dashboard—the owners of these affected components can easily notify downstream stakeholders. This proactive communication helps downstream asset owners understand the potential ripple effects of the changes, enabling them to take necessary actions to mitigate any disruptions or data quality issues.
Engineers now have the flexibility to update data lineage directly through APIs, bypassing the need for manual updates via the user interface. This streamlined approach saves time and enables seamless integration with existing workflows, allowing for faster and more efficient management of data lineage.
Choose which fields to monitor with 12 available test types such as null%, regex_match, cardinality etc.
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Thresholds for table tests such as Volume and Freshness are auto-detected by our system once data source is connected.
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Alerts are grouped so we don't spam you 100s of notifications. We also deliver them directly to your email or Slack.
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Always experience missing data? Check for data-diffs between any two datasets such as your staging and production tables.
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Automation of Monitors
Data Lineage
Their data contract module is amazing which virtualises and runs monitors.
Big fan of their UI/UX, it simple but managing all the complex task.
My team uses on a daily basis.
Seamless integration with all the data connectors. We also liked the new dbt-core connector directly integrated with Object storage.
Automated Column-Level lineage
Perfect blend of Data Catalog and Data Observability modules.
Business users are able to understand if the reports /dashboard have issues / incidents.
Personally liked the monitors by segment since we have mulitple business it provides incidents breakdown by attributes.
UX and UI, features, flexibility and excellent customer service. People like Manoj Matharu took the time to understand my business and data needs before trying to solution.
One of the best-designed data products. Our complete data infra is getting observed and governed by decube. My fav is the lineage feature which showcases the complete data flow across the components.
What I appreciate most about Decube is its intuitive design and the way it supports maintaining data trust. The platform allows for straightforward monitoring of data quality, making it easier to detect issues early on.One of the most valuable aspects is the transparency it brings to our data pipelines, which also streamlines collaboration among teams. The greatest benefit is the assurance that our data remains accurate, consistent, and prepared for decision-making, all without the need to spend countless hours troubleshooting.
Decube is packaged of solution for us. We were struggling to find one good tool in which we can intigrated with our existing data stack we are using mysql. As a DevOps we used to write crond jobs to check data quality but when we adapt this tool the work and quality both are improved. I highly recommend !
Data lineage shows the complete journey of data as it flows across different systems—from source to transformation to consumption. It matters because it helps organizations ensure accuracy, trace errors, meet compliance needs, and build trust in their data.
Key benefits include improved data quality, faster root-cause analysis, stronger compliance and audit readiness, better collaboration between business and technical teams, and increased confidence in AI and analytics initiatives.
Regulations like GDPR, HIPAA, and financial reporting standards require organizations to prove where data comes from, how it is transformed, and who has access. Data lineage provides the visibility needed to demonstrate compliance and reduce risk.
Common challenges include siloed systems, manual documentation, evolving pipelines, and incomplete metadata. Automated lineage tools help overcome these challenges by parsing queries, tracking dependencies, and keeping lineage up to date.
Modern data lineage platforms combine metadata management, query parsing, pipeline integration, and visualization. Advanced solutions (like Decube’s Data Trust Platform) provide end-to-end lineage across hybrid and multi-cloud environments, connecting both technical and business perspectives.
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