DQOps integration
DQOps integrates with multiple tools, using both the REST API interface and by using file formats based on open standards.
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DQOps provides operators for Apache Airflow for running data quality checks and the detecting the data quality status of a any table, before the table is used as a data source.
The DQOps Airflow operators can be used in a DAG before or after a data loading job. The DQOps operator can perform a circuit breaking to stop the pipeline, and prevent loading invalid data downstream when fatal severity issues are detected.
The DQOps Python package is available on PyPI.
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Data Quality Dashboards are a fundamental way to communicate the current state of data quality to stakeholders.
DQOps developed a custom Looker Studio Community Connector that accesses the data quality results in the user's private Data Quality Data Warehouse. When using DQOps connector, it is possible to customize built-in data quality dashboards or design custom dashboards that are better suited for the monitored data environment.
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Notifications of new or updated data quality incidents can be published to a Slack channel. DQOps also supports incident workflows, sending different messages to different channels. The notifications of new incidents can be sent to a data quality team, the data quality team evaluates the incidents and assigns the incident for resolution. The data engineering team receives a notification only about a verified data incident that needs resolving.
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YAML files used by DQOps to store the configuration of data sources and data quality checks are fully documented using a published YAML/JSON schema.
By installing a Visual Studio Code extension for editing YAML files, code completion, inline help about data quality checks and syntax highlighting is enabled.
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Any changes to the data quality incidents can be also published by posting the IncidentNotificationMessage message to a third-party listener.
The webhooks can be used to create and change the status of incidents created in issue management platforms, such as Jira, Azure DevOps, ServiceNow and others.