Databricks provides the scalable engine for data and AI, while dataspot. brings the semantic layer that makes data understandable, governable, and usable for everyone.

In today’s data-driven world, organizations don’t just need powerful platforms - they need clarity, trust, and collaboration across the entire data lifecycle. Together, they empower teams to turn raw data into reliable insights—faster, smarter, and with full transparency.

Databricks provides the Lakehouse architecture that unifies data engineering, data science, and machine learning on a single platform.

It enables:

Scalable data processing

Real-time analytics

Advanced AI/ML workloads

But as data volumes grow, so do the challenges of data discoverability, governance, and collaboration.

dataspot adds the semantic and governance layer on top of Databricks, making data:

Understandable through business-friendly metadata and data catalogs

Trustworthy via lineage, quality indicators, and ownership

Usable by everyone—from analysts to executives—through intuitive interfaces and collaboration features

Benefits:

Accelerated Time-to-Insight: Business users find and understand data without needing technical support.

Improved Data Trust: Lineage and quality indicators reduce risk in decision-making.

Stronger Data Culture: Everyone speaks the same data language—from engineers to executives.