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dbt is the standard for creating governed, trustworthy datasets on top of your structured data. MCP is showing increasing promise as the standard for providing context to LLMs to allow them to function at a high level in real world, operational scenarios. Today, we are open sourcing an experimental version of the dbt MCP server. We expect that over the coming years, structured data is going to bec
Dimensional modeling is one of many data modeling techniques that are used by data practitioners to organize and present data for analytics. Other data modeling techniques include Data Vault (DV), Third Normal Form (3NF), and One Big Table (OBT) to name a few. While the relevance of dimensional modeling has been debated by data practitioners, it is still one of the most widely adopted data modelin
dbt's node selection syntax makes it possible to run only specific resources in a given invocation of dbt. This selection syntax is used for the following subcommands: commandargument(s)
Why does structure matter? Analytics engineering, at its core, is about helping groups of human beings collaborate on better decisions at scale. We have limited bandwidth for making decisions. We also, as a cooperative social species, rely on systems and patterns to optimize collaboration with others. This combination of traits means that for collaborative projects it's crucial to establish consi
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