anomalyarmor
Official@anomalyarmor
Offers comprehensive data observability, schema drift detection, and lineage mapping for enterprise data assets and quality monitoring.
Agent Skills by anomalyarmor
Showing 14 vetted skills indexed across 1 GitHub repositories.
anomalyarmorarmor-monitor
Configure data freshness and schema drift monitoring with the AnomalyArmor Python SDK.
anomalyarmorarmor-test
Test and preview monitoring configurations for data assets.
anomalyarmorarmor-ask
Query data assets for schema, lineage, and metadata using natural language.
anomalyarmorarmor-quality
Create and manage data quality metrics and validity rules via the AnomalyArmor API.
anomalyarmorarmor-recommend
Analyzes data patterns and historical alerts to recommend monitoring configurations.
anomalyarmorarmor-investigate
Diagnose root causes of stale data and triggered alerts using lineage and historical monitoring data.
anomalyarmorarmor-status
Summarize data asset health with alerts, freshness, and schema drift.
anomalyarmorarmor-tags
Apply custom tags to tables and columns across data sources.
anomalyarmorarmor-alerts
Query and manage AnomalyArmor data alerts with filtering by time, severity, status, and asset ID.
anomalyarmorarmor-profile
Profile tables and columns for statistics, distributions, cardinality via AnacondaArmor API.
anomalyarmorarmor-lineage
Map upstream sources and downstream consumers of data assets.
anomalyarmorarmor-analyze
Analyze data assets to generate descriptions, infer types, and detect relationships.
anomalyarmorarmor-connect
Connects new data sources to AnomalyArmor via the Python SDK.
anomalyarmorcoverage
Analyze data monitoring configurations to identify assets lacking freshness, quality, or alert checks.
Frequently Asked Questions About anomalyarmor
FAQPage SchemaWhat specific data monitoring tasks does AnomalyArmor enable?▼
AnomalyArmor enables schema drift detection, data freshness monitoring, and quality metric management. It provides capabilities for profiling table statistics, mapping upstream and downstream lineage, and generating automated descriptions for data assets to ensure consistent health reporting across complex environments.
Which technical personas benefit from using AnomalyArmor?▼
Data engineers, database administrators, and analytics architects benefit from these capabilities. These personas use the platform to maintain data reliability, diagnose root causes of alert triggers, and ensure that data assets meet defined quality and freshness standards before being utilized by downstream consumers.
What are the prerequisites for integrating AnomalyArmor with existing data sources?▼
Integration requires connectivity to your data sources and the configuration of monitoring parameters via the provided interface. Users must define quality rules, freshness thresholds, and schema expectations to enable the system to profile assets, map lineage, and generate alerts based on historical patterns.