Data platforms & warehouses
Land Genesys Cloud operational KPIs in enterprise data platforms for historical analytics, ML and cross-domain reporting — without rebuilding Genesys ingestion per warehouse.
Operational truth and analytical history
Most programs keep an operational metrics store as the system of record for sub-minute metrics and a warehouse for long-horizon history, joins and ML features. Streamvane supports both from one Reactive Engine — and loads computed KPI semantics, not just raw exports.
Targets in this category
11 targets · 1 implemented / proven
Operational metrics store
Operational system of record for computed KPIs.
Snowflake
Snowpipe streaming or staged COPY loads.
Azure Synapse
Dedicated SQL pool warehousing.
Azure Data Factory
Orchestrated load pipelines.
Databricks
Delta Lake and Auto Loader.
Microsoft Fabric
OneLake lakehouse.
Amazon Redshift
COPY or streaming ingestion.
Google BigQuery
Streaming insert.
Azure SQL / SQL Server
Relational sink (legacy campaign patterns).
PostgreSQL
Open-source RDBMS sink.
Delta Lake on ADLS
File-based lakehouse landing.
Why it matters
Warehouse-grade Genesys history
Warehouses need consistent, well-defined, time-series metrics — not ad-hoc CSV dumps that drift from the operational definition.
Curated KPIs, not just raw data
iPaaS and ETL tools load Genesys raw data. Streamvane loads computed KPI semantics — the metrics WFM and operations already agreed. Often both coexist: raw in the lake, curated KPIs in warehouse tables ready for reporting and ML.
- Micro-batch export or streaming insert via Snowpipe / Synapse
- File landing as Parquet for lakehouse Auto Loader
- Same definition as dashboards and operational feeds
Choosing
Operational vs analytical layers
Two layers, one Reactive Engine.
| Layer | Role | Connector |
|---|---|---|
| Operational | Sub-minute computed metrics | Operational store (today) + streaming connectors |
| Analytical | Interval history, joins, ML features | Warehouse packages + batch / file connectors |
Same engine, same guarantees
Every target inherits the platform
Whichever destination you pick, it runs on the same Reactive Engine — with consistent semantics, client-owned Azure, enterprise security and a delivery lifecycle that fits your estate.
One KPI definition
Every target in this category consumes the same computed metrics — service level is service level, everywhere.
Client-owned Azure
Ingest, reactive processing and storage run inside your subscription. Connectors are the only thing that reaches outward.
Platform-package model
Each target ships as a Global.Platform.* package on the shared core — adding one is a connector, not a rewrite.
Built for your SDLC
Provisioned as code, shipped through your pipelines, secured in Key Vault — like any other service you run.
Map your destinations to the right connectors
Book a connector assessment and we'll match your KPI families to the targets in this category — on your own Azure tenant.
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