KPIet

KPIet is a modular software framework designed to define, compute, and visualize key performance indicators (KPIs) across organizations. It emphasizes consistent KPI definitions, data provenance, and automated reporting to help teams monitor performance and drive data-informed decisions.

Architecture and components: data connectors, KPI definitions, calculation engine, dashboards, and alerting. KPI definitions use a declarative format (YAML or JSON) that captures metadata, data sources, calculation formulas, time grain, targets, and thresholds. The calculation engine supports time-series operations, baselining, rolling aggregates, and rule-based alerts. Data can be sourced from relational databases, data warehouses, streaming platforms, or REST endpoints, and results can be published to dashboards, exported reports, or notification channels.

Data model and governance: Each KPI records metadata such as owner, lineage, data sources, version, and lineage. KPI hierarchies enable rollups and attribution across organizational structures. The platform provides audit logs, role-based access control, and versioning to support governance and reproducibility.

Deployment and ecosystem: KPIet is designed as an open-source framework that can be deployed on premises or in the cloud. It supports containerized deployments, CI/CD integration, and a plugin API for connectors, visual widgets, and data transforms. A community-driven ecosystem offers templates for common KPI definitions and dashboards.

Usage and reception: Organizations use KPIet to standardize KPI definitions, reduce spreadsheet-based silos, and automate KPI refreshes. Critics note potential complexity and reliance on data quality, requiring robust data governance and data engineering resources.