Business Analytics

Business analytics is the practice of turning raw data into actionable insight. It spans descriptive analytics (what happened), diagnostic analytics (why it happened), predictive analytics (what will happen), and prescriptive analytics (what to do about it). The common thread is replacing gut feeling with evidence drawn from operational, behavioral, and market data.

For software companies, analytics informs product decisions — feature adoption rates, conversion funnels, performance budgets, and churn prediction. Distributed engines like Apache Spark and Flink handle the processing, while visualization tools make results accessible to non-technical stakeholders.

Open-source business intelligence platforms:

Metabase — query databases and build dashboards without SQL knowledge. Embeddable analytics. Enterprise adds SAML, row-level security, and white-label embedding. AGPL v3.

Apache Superset — enterprise-grade data exploration and visualization with 40+ chart types. Connects to most SQL databases. No feature gating. Apache 2.0.

Lightdash — dbt-native BI tool. Turns dbt models into explorable dashboards. Enterprise features require license key for self-hosted. MIT.

Cube — universal semantic layer between data sources and BI tools. Core is fully open; cloud adds managed deployment and observability. Apache 2.0.