Cube Dev Inc., the creator of an open-source semantic layer that simplifies access to data from disparate systems, is launching an “agentic analytics” platform that uses artificial intelligence to ...

Now that we have a rough idea of where a data model fits within the vast data landscape, let’s explore what it can achieve from its position on the semantic floor. If you were to embody a data model, ...

and context that go into a semantic data model. They start by understanding the real-world problems that the business needs to solve, gathering the necessary data, and then encoding the ...

In addition, many business users think of data modeling as something strictly technical and dependent on in-depth coding skills. Semantic sprawl exacerbates the problem. Another barrier to ...

Cube competes with AtScale, which also offers a semantic layer for data modeling and serving, and Dtb Labs’ recently acquired Transform. But Cube appears to be holding its own, with a customer ...

These new capabilities tightly integrate with AtScale’s existing no-code visual modeling framework and provide flexibility to build and manage data models and metric definitions within the semantic ...

At first glance, building a large language model (LLM) like GPT-4 into ... i.e. the native computer code that processes data for use in the LLM’s semantic functions. Outputs of one function ...

Implementing the semantic layer using transformation services The set of transformation services in the A16Z data stack includes metrics layer, data modeling, workflow management and entitlements ...

How well an ML model performs is directly dependent ... Finally, by leveraging data lineage and semantic descriptions, businesses will be able to fully understand the lifecycle of all data and ...