Redbird AI automates the data pipeline between Google's cloud warehouse and Microsoft's analytics platform. Stop manually exporting CSV files, scheduling refresh scripts, and wrestling with connector limitations. Let AI handle dataset synchronization, schema mapping, and dashboard updates across your GCP and Microsoft stack.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Detect when critical BigQuery tables are modified or new data arrives. Trigger incremental or full refresh of corresponding Power BI datasets without manual intervention. Keep dashboards current without fixed schedules or stale data risk.
When data engineers create new summary tables or materialized views in BigQuery, automatically create corresponding Power BI datasets with proper relationships and data types. Redbird maps BigQuery schemas to Power BI semantic models, maintaining consistency across your analytics stack.
Execute parameterized BigQuery SQL queries based on business logic or schedules. Route results directly to targeted Power BI datasets or DirectQuery connections. Enable department-specific views without duplicating warehouse queries or building complex dataflows.
Monitor Power BI DirectQuery performance metrics and identify slow-running queries hitting BigQuery. Analyze query patterns and recommend specific BigQuery partitioning, clustering, or indexing strategies. Surface optimization opportunities before users complain about dashboard load times.
Capture which reports are viewed, filters applied, and drill-through paths users take in Power BI. Write this interaction data to BigQuery tables for analysis alongside usage data from other tools. Build comprehensive analytics on analytics platform adoption and report effectiveness.
Query BigQuery ML models on-demand from Power BI user interactions or scheduled refreshes. Inject prediction scores, classification results, or forecasts directly into Power BI datasets. Surface machine learning insights in business dashboards without separate ML infrastructure.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Power BI 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 AI understands both BigQuery's columnar storage architecture and Power BI's semantic modeling layer, automatically translating between GCP data types and Microsoft's analytics schemas.
Redbird reads BigQuery table schemas, partitioning strategies, and nested/repeated fields, then maps them intelligently to Power BI data models with proper relationships and aggregations. The AI recognizes when to use DirectQuery versus Import mode based on dataset size and refresh requirements. It handles TIMESTAMP conversions, ARRAY field flattening, and GEOGRAPHY type transformations automatically, eliminating the manual data type wrestling that breaks most BigQuery-to-Power BI connections.
faster than building custom Python scripts with BigQuery and Power BI REST APIs
Redbird can pull from BigQuery and Power BI 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 BigQuery or Power BI.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from BigQuery into Power BI, or from Power BI back into BigQuery. 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 automations from BigQuery table updates, query completions, or Power BI refresh events, then take action in either system.
Fires when rows are inserted, updated, or deleted in a specified BigQuery table or partition.
Triggers when a BigQuery scheduled query finishes running, whether successful or failed.
Detects when a new BigQuery dataset is added to your GCP project.
Execute parameterized SQL queries against BigQuery and return results for downstream processing.
Write data to BigQuery tables with automatic schema detection or specified column definitions.
Run BigQuery SQL and export results to Cloud Storage, formatted for Power BI import.
Fires when a Power BI dataset finishes refreshing, including success/failure status and row counts.
Triggers when users publish new Power BI reports or update existing ones in a workspace.
Activates when Power BI data-driven alerts detect metric thresholds or anomalies in dashboard tiles.
Trigger full or incremental refresh of Power BI datasets on-demand, bypassing scheduled refresh limits.
Modify Power BI dataset connection strings, query parameters, or data source credentials programmatically.
Generate new Power BI reports from templates with dynamic data sources and publish to specified workspaces.
Redbird AI syncs BigQuery and Power BI in minutes, not weeks. Stop building and maintaining custom integration scripts—let AI handle the data pipeline between your Google warehouse and Microsoft dashboards.