Overcoming data inconsistency with a universal semantic layer



Once the underlying data and semantics are established, the universal semantic layer must be integrated with data consumers, such as generative AI, BI, spreadsheets, and embedded analytics. Cube Cloud is a universal semantic layer platform offering numerous prebuilt integrations and a robust API suite so enterprises can model data once and deliver it anywhere. It also offers a host of developer tools to make it easier to collaborate and build data models, set up caching and pre-aggregations, and maintain data access controls.

Benefits of a universal semantic layer

With a universal semantic layer, data teams have more governance and control, and — if implemented correctly — end users get more value from data and fewer misunderstandings among teams. This enhances efficiency and ensures that all data consumption places are working with the same, accurate data. So, no matter if the data is being used by a person looking at a dashboard, or a large language model that is giving someone answers to questions, the data is consistent.

All of this makes it easier for data teams to quickly deliver data to the various consumers they work with internally and externally. Data teams can easily update or define new metrics, design domain-specific views of data, and incorporate new sources of raw data. They also can enforce governance policies, including access control, definitions, and performance.



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