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Quickstart stack

An analytics and BI starter stack: the smallest useful one

Seven tools and eight connections: collect with Tag Manager and GA4, store in BigQuery, model with dbt, and report in a BI tool. Most stacks start here, before there is anything to activate.

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7 tools · 8 connections

OneTrust to Google Tag Manager: Consent modeOneTrust to Google Analytics 4: Consent stateGoogle Tag Manager to Google Analytics 4: Tagged pageviewsGoogle Analytics 4 to BigQuery: BigQuery ExportBigQuery to dbt: Raw tablesdbt to BigQuery: Modelled martsBigQuery to Power BI: Semantic model refreshBigQuery to Tableau: Live extract refresh OneTrust Consent Management dbt Data Modeling Power BI Analytics & BI Google Tag Manager Tag Management Google Analytics 4 Analytics & BI BigQuery Data Warehouse Tableau Analytics & BI
Scroll sideways to see the whole stack. Arrows show the direction data moves. Every connection is listed by name below.

What it is for

Use it when the job is reporting you can trust: one place for the data, models in version control, and dashboards that read the models rather than the raw export.

It carries both Power BI and Tableau on purpose. Most teams end up with two BI tools, and the Stack Audit flags the pair as overlapping, which is a useful thing to see on a stack this small.

Why each tool is here

  • OneTrust Consent Management

    Consent management. It records what each visitor agreed to and passes that state on, so the tools downstream only collect and use what they are allowed to.

  • Google Tag Manager Tag Management

    Tag management. Fires the GA4 tags.

  • Google Analytics 4 Analytics & BI

    Web analytics, and the source of the raw events the warehouse receives.

  • dbt Data Modeling

    Data modeling. Turns the raw GA4 export into marts the BI tools can read, in SQL with tests.

  • BigQuery Data Warehouse

    The warehouse. Raw events in, modeled marts out.

  • Power BI Analytics & BI

    BI, through a semantic model refreshed daily.

  • Tableau Analytics & BI

    BI as well, refreshed hourly. The second BI tool is the overlap the audit points at.

How data flows

Tag Manager sends pageviews to GA4, with OneTrust setting consent on both. GA4 exports to BigQuery daily. dbt reads the raw tables and writes modeled marts back to BigQuery, and both BI tools read the marts.

Every connection

  1. OneTrust to Google Tag Manager Consent mode · Real time, on each event
  2. OneTrust to Google Analytics 4 Consent state · Real time, on each event
  3. Google Tag Manager to Google Analytics 4 Tagged pageviews · Streaming, continuously
  4. Google Analytics 4 to BigQuery BigQuery Export · Batch, daily
  5. BigQuery to dbt Raw tables · Batch, daily
  6. dbt to BigQuery Modelled marts · Batch, daily
  7. BigQuery to Power BI Semantic model refresh · Batch, daily
  8. BigQuery to Tableau Live extract refresh · Batch, hourly

When this is the wrong choice

  • You need to act on the data, not only report on it. There is no activation here; the Google-native quickstart adds the ad platforms.
  • Nobody on the team writes SQL. dbt is the piece that makes the reporting trustworthy, and it needs an owner.

Try this: Open it and run the Stack Audit: Power BI and Tableau should come back as overlapping.

Other quickstart stacks

Make this stack yours

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