No-nonsense Data Quality Monitoring
Dragonfly Data HQ ensures data integrity and quality in real-time data pipelines.
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Dragonfly Data HQ ensures data integrity and quality in real-time data pipelines.
Watch 2-minute Demo Request A Demo
Analyze datasets as they are processed, detect issues, and prevent data corruption before it impacts your reports.
Tailor Dragonfly with custom data quality checks and templates to enhance error detection capabilities.
Generate comprehensive Data Confidence Reports by performing quality checks on your data.
Discover the robust features that make Dragonfly a top-tier data quality monitoring tool.
Receive instant alerts when data issues occur, ensuring reliable data processing.
Prevent data corruption by halting data processing when issues are detected.
Choose from a library of quality rules across data sources and stages.
Easily integrate Dragonfly into existing pipelines using our extensive APIs, and Warehouse and Data Lake integrations.
Choose what access you share with Dragonfly and what Metadata is captured, or use access-less integrations.
Stay informed of the quality issues via SMS, email, or a workflow management system.
Each data processing step is identified as a process. Each stage the data goes through, like ingestion, processed and report is identified as a component. Each type of component has expected behaviour and quality check types in Dragonfly.
Relationships between the components show the interdependence of the components fot the purpose of calculating the quality. This is by nature the inverse order of execution represented by the orchestrator tools like Apache Airflow.
A pipeline is a logical representation of the data processing pipeline, represented as a DAG. Pipelines in Dragonfly are more nuanced than those in orchestration tools like Apache Airflow, in the sense that they also represent logica groups and stages.
As tests, they are executable expectations of the data quality. There is a library of checks to choose from. There are some built-in checks based on the component type. And it is possible to write your own.
A quality rating generated by Dragonfly based on the checks applied. It is a comprehensive metrics calculated by weighted resolution of ratings of all dependencies and checks applied.
Import the processing stages as components and connect them to build pipelines.
Choose form the library, ask the Dragonfly GPT or Write your own checks.
Experience heightened confidence in your data with our precision-assured reports.