The text discusses the integration of dlt and dbt tools in solving data flow problems, particularly in creating a modern data stack through modular components. `dlt` automates data cleaning and normalization, while `dbt` simplifies sources by creating SQL models that simplify data structures. The semantic layer of `dbt` enables central metric definitions, allowing for uniform metric definitions to be handled centrally and ensuring data democracy practices in companies. The tools are demonstrated through a pipeline example, where `dlt` extracts and loads data into BigQuery, and `dbt` transforms the data and creates metrics.