No plugins, no config. Visibility is built into every layer of your data pipelines.
Instantly trace where data came from and what it affects — without extra tools.
Spot patterns and regressions over time with detailed performance history.
Automatically log every config change, failure, and data quality result.
Run validations anywhere, define rules, and control how your system responds to failures.
Ascend provides live runtime metrics like task duration, success/failure rates, and resource usage — so you can catch issues before they impact downstream systems.
Run data quality checks on any component —including at the point of ingestion. Define your own data quality rules, and dictate whether failures trigger alerts, block execution, or automatically retry — so bad data never slips through.
Ascend gives you end-to-end visibility across your pipelines with automatic lineage and version history. Track every transformation, schema update, and config change to quickly trace the impact and resolve issues faster.
Configure alerts for pipeline failures, slow runs, data quality test failures, and more. Set thresholds that matter to your team, and trigger Slack, email, or webhook notifications — so you can act before downstream users feel the impact.
Ascend keeps a detailed history of your pipeline performance, data quality checks, and system events — so you can identify recurring failures, regressions, or bottlenecks over time. Use past data to improve future reliability.
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We developed a framework with a sequence of stages to implement data integrity quickly and measurably via data pipelines.
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Explore the complexities of data replication strategies in a way that's easy to understand, including types and how to choose the right one.
Explore how to build a data pipeline in 6 steps, from design to deployment, and learn a new framework to simplify the process.
