Sync Piano Analytics audience data into Databricks for advanced analysis, or push ML predictions and enriched user segments back to Piano. Stop manually exporting CSVs, writing one-off ETL scripts, and waiting on data teams to connect behavioral analytics with your lakehouse.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Capture raw event data, page views, and user sessions from Piano Analytics and load them incrementally into Databricks Delta Lake. Redbird handles schema evolution, deduplication, and partition management so your data engineering team can focus on transformation and modeling instead of maintaining ingestion pipelines.
Use ML models trained in Databricks to generate subscriber churn risk scores, content affinity predictions, or propensity-to-convert metrics. Redbird automatically pushes these predictions back to Piano Analytics as custom properties or segments, enabling your editorial and product teams to act on ML insights without leaving their analytics platform.
Merge Piano Analytics clickstream and conversion events with CRM data, payment history, and content metadata stored in Databricks. Redbird joins datasets intelligently across user IDs and timestamps, creating a complete view of subscriber behavior that spans multiple systems and teams.
Automatically kick off Databricks notebooks or workflows when Piano Analytics identifies viral content, traffic anomalies, or conversion funnel changes. Use these triggers to refresh recommendation models, recalculate audience segments, or generate automated reports that surface what's driving engagement in near real-time.
Export user-level features from your Databricks Feature Store—like content consumption history, topic preferences, or engagement patterns—directly into Piano Analytics as custom dimensions. Marketing and product teams can then segment audiences and personalize experiences based on the same ML features powering your models.
Automatically export and archive Piano Analytics raw event data beyond platform retention limits into cost-effective Databricks storage. Maintain complete historical records for multi-year trend analysis, regulatory compliance, and model training while keeping Piano Analytics optimized for real-time reporting.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and Piano Analytics 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 Databricks lakehouse schemas and Piano Analytics event taxonomies, so you can connect behavioral analytics with advanced data engineering without custom code.
Redbird automatically maps Piano Analytics event properties, custom dimensions, and user identifiers to your Databricks Delta table schemas. It understands Piano's privacy-first visitor IDs, session structures, and content hierarchies, and intelligently translates them into optimized lakehouse formats. Whether you're working with Piano's page.display events, conversion funnels, or custom properties, Redbird handles type casting, nested JSON parsing, and incremental updates without manual schema definitions.
faster than building custom Spark jobs to ingest Piano Analytics data
Redbird can pull from Databricks and Piano Analytics 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 Databricks or Piano Analytics.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Databricks into Piano Analytics, or from Piano Analytics back into Databricks. 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 any Databricks job, table change, or Piano Analytics event—then take action across both systems.
Trigger when new data is written to a specific Delta table or partition in your Databricks lakehouse.
Start workflows when a scheduled notebook, pipeline, or MLflow model training run finishes successfully.
Detect when a new model version is registered in MLflow or promoted to production stage.
Execute a specific notebook with parameters, passing in data from Piano Analytics or other systems.
Insert or merge rows into a Delta Lake table with automatic schema handling and deduplication.
Kick off a Databricks workflow, Delta Live Tables pipeline, or scheduled job on-demand from external events.
Trigger when Piano Analytics captures new page.display events, sessions, or user interactions above a threshold.
Start workflows when users complete subscription sign-ups, paywall conversions, or custom goal events in Piano.
Detect when a behavioral segment in Piano Analytics crosses a defined size or engagement threshold.
Write custom dimensions or user-level attributes into Piano Analytics profiles from ML models or enriched datasets.
Programmatically build audience segments in Piano based on predictions, classifications, or data from Databricks.
Pull raw event streams, aggregated metrics, or custom reports from Piano Analytics into your data workflows.
Sync Databricks with Piano Analytics in minutes. Stop writing custom ingestion scripts and start building ML-powered analytics workflows that actually ship.