Elementary Data

Elementary Data is an automated data quality monitoring and anomaly detection tool for dbt projects, with AI agents for end-to-end data reliability workflows.

Key Features

• Automated anomaly detection: Automatically detects data anomalies and monitors dbt model execution time and run results.
• AI agents: AI agents can access BI information and data warehouse metadata from the information schema, including volume and freshness metrics and query history, supporting end-to-end workflows.
• Integrations and alerts: Fivetran sync failures trigger alerts to Slack, Teams, or any configured destination; Jira integration allows editing and adding more details to tickets before creating them.
• Self-serve configuration: Supports self-serve setup of multiple dbt projects in a single Elementary workspace; all configurations, descriptions, tags, and owners are managed in dbt code, enabling version control, code review, and CI/CD.
• Permission management: Elementary Cloud supports role-based access management with clear control over who can access what.
• Incident management: Redesigned incidents page with an improved configurable layout; tables returned in agent chat can be downloaded as CSV.

Target

Audience Data engineers, dbt users, analytics engineers, and data teams.