Loading…
What is enterprise intelligence?
Databricks Staff
- Source
- Databricks
- Published
- Added to Yomu
Summary
Enterprise intelligence (EI) is presented as an organization-wide capability combining business intelligence, knowledge management, enterprise search and AI to turn structured and unstructured data into decisions and actions. Unlike traditional BI, which centers on dashboards, reports and structured data, EI connects these capabilities through a shared architecture and governed business context. The described stack includes a lakehouse-based data foundation, batch and streaming pipelines, governance, semantics, analytics, search, machine learning, generative AI and a decision layer. Shared definitions such as “active customer” and “monthly revenue” are intended to keep dashboards, queries and AI agents aligned, while maintained context addresses knowledge that becomes stale as the business changes. The result described is a common trusted source from which people, applications and agents can produce insights and initiate actions.
Context
Organizations hold both structured and unstructured information across different systems, while teams may use inconsistent business definitions and stale organizational knowledge. Enterprise intelligence addresses the need for reliable answers, consistent metrics and decisions that can be acted on by people, applications and AI systems.
Approach / What changed
The approach combines a lakehouse data foundation, batch and streaming pipelines, governance, shared business semantics, analytics, enterprise search, knowledge management, predictive and generative AI, and a decision layer. These components work from a shared governed data layer, with tools including Unity Catalog Business Semantics, Lakeflow, Genie and Databricks Agent Bricks described as supporting the architecture.
Takeaways
- Governance and business semantics serve different but complementary roles: governance controls access and lineage, while semantics define shared meanings for metrics, dimensions and business terms.
- Enterprise intelligence treats documents, emails, contracts, support logs, images and call transcripts alongside database records as first-class information sources.
- AI systems and agents depend on current organizational context; static documentation and infrequently updated definitions can become inaccurate as products, pricing, regulations and customer segments change.