Automate the flow between your operational Azure SQL databases and Looker analytics layer. Stop manually syncing schemas, rebuilding LookML models when tables change, or writing custom ETL scripts to keep your BI reporting current with production data.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
When tables, columns, or data types change in Azure SQL, Redbird automatically updates corresponding LookML views and dimensions. Your Looker semantic layer stays in sync with production schema evolution without manual LookML refactoring or data team intervention.
Redbird compares LookML measures and dimensions against Azure SQL schema metadata, foreign keys, and constraints. Catch metric definitions that reference dropped columns, incorrect joins, or data type mismatches before they break dashboards in production.
When developers add new tables or modify stored procedures in Azure SQL, Redbird analyzes the schema and generates baseline LookML view files with appropriate dimensions and joins. Analytics engineers get a head start on exposing new data sources to business users.
When Looker Explores surface anomalies, duplicates, or incomplete records through data quality dashboards, Redbird moves flagged rows to Azure SQL archive tables. Keep production databases clean while preserving audit trails for compliance and troubleshooting.
When KPIs in Looker dashboards cross defined thresholds—like inventory falling below reorder points or SLA breach indicators—Redbird writes status flags back to Azure SQL. Operational systems can react to analytical insights without custom integration code.
Redbird takes cohort definitions and customer segments calculated in Looker—lifetime value tiers, engagement scores, churn risk—and writes them back to Azure SQL customer tables. Power personalization, marketing automation, and operational workflows with analytics-derived attributes.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Azure SQL and Looker with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands both Azure SQL's relational structure and foreign key relationships, and Looker's LookML semantic layer with its explores, joins, and derived tables.
Redbird parses Azure SQL system catalogs to understand tables, indexes, constraints, and stored procedures—then maps them to Looker's LookML views, explores, and join logic. The AI recognizes when a LookML dimension references a renamed Azure SQL column, when a new table should become an explore, or when data types have diverged. No manual field mapping or brittle column name matching required.
faster than building custom sync scripts between Azure SQL and Looker
Redbird can pull from Azure SQL and Looker simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Azure SQL or Looker.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Azure SQL into Looker, or from Looker back into Azure SQL. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start workflows from schema changes in Azure SQL or metric updates in Looker—Redbird connects both systems in either direction.
Fires when columns are added, removed, or data types change in tracked Azure SQL tables.
Triggers when a new table appears in specified Azure SQL databases or schemas.
Detects when stored procedure definitions change, affecting downstream reporting logic.
Run SELECT, UPDATE, or stored procedure calls against Azure SQL with dynamic parameters.
Write new rows or update existing records in Azure SQL tables based on workflow data.
Move records matching criteria to archive tables while maintaining referential integrity.
Fires when a LookML project is deployed to production, signaling new metric definitions.
Triggers when a dashboard visualization crosses defined KPI limits or anomaly thresholds.
Detects when Looker Explores produce SQL errors, often indicating schema drift.
Modify dimension, measure, or join definitions in LookML files via Git integration.
Create a new LookML explore with specified base views and join paths.
Trigger rebuild of Looker Persistent Derived Tables to reflect updated source data.
Connect Azure SQL and Looker in minutes. Let Redbird automate schema sync, metric validation, and bi-directional data flows so your analytics layer stays current with operational reality.