Data Quality & Observability — Workshop Lab Materials

Module 2: Practitioner (4 hours). Companion to the Xebia Foundation Data Quality & Observability training.

Prerequisites

• uv
• Git

uv manages Python automatically — no separate Python installation needed.

Setup (do this before the session)

1. Clone this repo

git clone <repo-url>
cd dq-observability-workshop

2. Install dependencies

uv sync

3. Install dbt packages and build the project

uv run dbt deps
uv run dbt seed
uv run dbt run

You should see PASS=6 — all 6 models built. The repo includes profiles.yml, so no dbt profile setup is needed.

4. Verify setup

uv run soda scan -d workshop -c labs/lab3_soda/configuration.yml labs/setup_check.yml

You should see 1/1 checks PASSED. You're ready.

Note: the sample data contains deliberate quality problems — that's the point of the labs. Don't fix them.

Labs

Lab	Topic	Duration	Folder
Lab 1	dbt Tests	50 min	labs/lab1_dbt_tests/
Lab 2	Contracts & Semantic Layer	40 min	labs/lab2_contracts/
Lab 3	Soda Checks	65 min	labs/lab3_soda/
Lab 4	Lineage & Blast Radius	35 min	labs/lab4_lineage/
—	Implementation Planning	20 min	labs/implementation_planning/

Solutions are in solutions/. Try not to peek until you've given it a go.

The DAG

raw_customers ──► stg_customers ──► customers (mart)
                               └──► customer_lifetime_value (mart)

raw_orders ──► stg_orders ──► int_order_summary ──► customer_lifetime_value
                         └──► orders (mart)