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Demo - Exploring the TPC-DS Dataset

Nov 25, 2024 - trilogydata.dev
The article provides a detailed guide on using Trilogy, a tool that allows users to query databases using a semantic layer. It explains how to use the TPD-DS dataset for transactional database benchmarking with DuckDB and how to explore the language syntax. The article also provides examples of basic queries, model definitions, derived concepts, filtering, and state aggregation. It also discusses the use of query merges and model merges to combine different models and concepts.

The article further explains how to save results using the 'persist' keyword and introduces TrilogyT, an integration that supports ETL workflows. It also highlights the benefits of a semantic layer and introduces Trilogy-NLP, which adds natural language processing to Trilogy. The article concludes with a comparison of SQL and Trilogy queries using the TPC-DS benchmark.

Key takeaways:

  • The demo uses the TPD-DS dataset for transactional database benchmarking and focuses on how DuckDB can produce a representative data warehouse for TPC-DS.
  • Trilogy is database agnostic and can work on any backend such as Postgres, Bigquery, or Snowflake.
  • Trilogy allows for the creation of models that define names and relationships for intuitive access to data, and these models can be used to generate queries.
  • Trilogy also supports ETL workflows and integrates with DBT for a full data warehouse workflow, and it can be used to create or update tables for powering dashboards.
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