When comparing analytics approaches, the difference between data warehousing and business intelligence boils down to where truth is created versus how it is consumed. A data warehouse is the governed source of curated, historical, and modeled data. Business intelligence (BI) is the layer that packages that data into dashboards, reports, alerts, and self-service analysis for day-to-day decisions.

Data warehousing centralizes cleansed data from multiple systems and enforces schema-on-write (model before expose). Teams build Star/snowflake schemas, encode business rules, and publish conformed dimensions and fact tables so metrics are consistent across the organization. If you need a refresher on analytics basics, start with NuSummit’s primer, What is Data Analytics?

BI sits on top of the warehouse and adds a semantic layer (shared KPIs), governed datasets, visualization, and distribution (dashboards, schedules, alerts). Learn more: Explore services. and Read the guide.