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Tableau tends to have stronger native visualization depth and a bigger enterprise analytics footprint; Power BI is usually the more natural fit for organizations already standardized on Microsoft 365.",{"question":427,"answer":428},"Do I need dbt, or can Tableau transform the data itself?","Tableau can do light transformation in its own layer, but pushing it into dbt instead keeps the logic version-controlled, testable, and reusable by any other tool that queries the same Snowflake models.",{"question":430,"answer":431},"Should Tableau use live connections or extracts against Snowflake?","Mostly extracts, and the reason is Snowflake's bill. A live connection sends a query to Snowflake every time someone opens a dashboard or clicks a filter, which keeps a warehouse running through the working day. An extract copies the data into Tableau on a schedule, typically right after the nightly dbt run, so viewers query Tableau and Snowflake compute runs only during the refresh. Keep live connections for the few dashboards that genuinely need fresh data, point them at a small dedicated warehouse, and set that warehouse to auto-suspend after a minute of inactivity. Separate warehouses for loading, transformation, and BI also show you exactly which layer the credits go to.",{"question":433,"answer":434},"What runs dbt after Airbyte loads new data?","Something outside both tools. Airbyte loads raw tables into Snowflake but doesn't start the dbt run afterwards, and dbt Core has no scheduler of its own. Three common answers: dbt Cloud, which adds a scheduler, a browser IDE, and job history on a per-seat plan; a scheduled CI job (GitHub Actions or GitLab CI) that runs dbt build at a fixed time after the sync window; or an orchestrator such as Airflow that waits for the Airbyte sync to finish, then runs dbt, then refreshes Tableau extracts. Fixed-time scheduling is fine while syncs finish predictably; once a late sync starts producing half-updated dashboards, it is time for an orchestrator.",{"question":436,"answer":437},"How is this different from the Modern ELT Stack?","Both load data with Airbyte into Snowflake and transform it with dbt. They differ at the ends: this stack finishes with Tableau, so business users get governed dashboards, and it leaves scheduling open; the Modern ELT Stack adds Airflow to orchestrate the pipeline in Python and leaves the choice of BI tool to you. Pick this stack when the goal is dashboards for many business users; pick the Modern ELT Stack when pipeline reliability, dependencies, and many scheduled jobs are the harder problem. Larger teams often end up with both: Airflow running the pipeline and Tableau on top.",{"summary":439,"starting_cost_label":440,"has_free_tier":3,"line_items":441},"Airbyte and dbt Core are free to self-host, and Snowflake bills by compute-second usage rather than a flat fee. Tableau is the fixed recurring cost: Creator seats (needed to build dashboards) start at $70\u002Fuser\u002Fmonth, with cheaper Viewer ($15) and Explorer ($42) seats for people who only consume them.","From ~$70\u002Fuser\u002Fmo (Tableau) + Snowflake usage",[442,445,448],{"label":352,"cost":443,"note":444},"$15-70\u002Fuser\u002Fmo","Creator seats ($70\u002Fmo) are needed to build dashboards; Viewer ($15\u002Fmo) and Explorer ($42\u002Fmo) cover people who only consume them.",{"label":240,"cost":446,"note":447},"Usage-based, ~$100+\u002Fmo","Billed by compute-second and storage; cost scales with data volume and query frequency.",{"label":449,"cost":450,"note":451},"Airbyte, dbt Core","Free (open source)","Both are free to self-host; Airbyte Cloud starts at $10\u002Fmo if managed hosting is preferred over self-hosting.","dashboard",{"title":454,"description":455,"og_image":32,"canonical":456},"Airbyte + dbt + Snowflake + Tableau: Tools, Pricing & How to Deploy | Tekyous","Modern cloud data stack: Airbyte ingests, dbt transforms, Snowflake stor… Compare Airbyte + dbt + Snowflake + Tableau tools, pricing & how to deploy on Tekyous.","https:\u002F\u002Ftekyous.dev\u002Fstacks\u002Fairbyte-dbt-snowflake-tableau",1790518792877]