# Databricks Retail Pipeline Screenshot Runbook Use this runbook to recreate the project later and capture proof of each step. Each step includes: - what to do - exact command or Databricks UI action - expected result - screenshot file to save Save screenshots in: ```text databricks-retail-pipeline/docs/screenshots/ ``` Recommended screenshot format: PNG. ## Screenshot Checklist | Step | Screenshot file | Status | | --- | --- | --- | | 01 | `01-winget-install-databricks-cli.png` | Captured from local install output if needed | | 02 | `02-databricks-cli-version.png` | Ready to capture locally | | 03 | `03-databricks-auth-login.png` | Capture after workspace login | | 04 | `04-current-user.png` | Capture after auth verification | | 05 | `05-project-folder.png` | Capture local project files | | 06 | `06-upload-csv.png` | Capture CSV upload command or Databricks UI | | 07 | `07-bundle-validate.png` | Capture `bundle validate` success | | 08 | `08-bundle-deploy.png` | Capture `bundle deploy` success | | 09 | `09-job-run.png` | Capture `bundle run` or Databricks job run | | 10 | `10-delta-tables.png` | Capture Databricks Catalog tables | | 11 | `11-quality-checks.png` | Capture SQL query results | ## Step 01: Install Databricks CLI Open PowerShell and run: ```powershell winget install Databricks.DatabricksCLI --accept-package-agreements --accept-source-agreements ``` Expected result: ```text Successfully installed ``` Screenshot to save: ```text docs/screenshots/01-winget-install-databricks-cli.png ``` ![Step 01 Databricks CLI install](screenshots/01-winget-install-databricks-cli.png) Local note from this machine: ```text DatabricksCLI 1.3.0 was installed successfully using winget. ``` ## Step 02: Verify Databricks CLI Open a new PowerShell window and run: ```powershell databricks -v ``` If PATH has not refreshed yet, run: ```powershell & "$env:LOCALAPPDATA\Microsoft\WinGet\Links\databricks.exe" -v ``` Expected result from this machine: ```text Databricks CLI v1.3.0 ``` Screenshot to save: ```text docs/screenshots/02-databricks-cli-version.png ``` ![Step 02 Databricks CLI version](screenshots/02-databricks-cli-version.png) ## Step 03: Authenticate To Databricks Replace the host with your own Databricks workspace URL: ```powershell databricks auth login --host https://YOUR-WORKSPACE-URL ``` Expected result: - Browser opens for Databricks login. - PowerShell returns to the prompt after authentication succeeds. Screenshot to save: ```text docs/screenshots/03-databricks-auth-login.png ``` ![Step 03 Databricks auth login](screenshots/03-databricks-auth-login.png) Do not include tokens or secrets in the screenshot. ## Step 04: Verify Current User Run: ```powershell databricks current-user me ``` Expected result: ```text User profile details from the authenticated Databricks workspace. ``` Screenshot to save: ```text docs/screenshots/04-current-user.png ``` ![Step 04 current user](screenshots/04-current-user.png) Blur or crop private email addresses if you share this publicly. ## Step 05: Review Project Files From the repository root: ```powershell Get-ChildItem -Recurse databricks-retail-pipeline | Sort-Object FullName ``` Expected project files: ```text databricks-retail-pipeline/ README.md databricks.yml data/retail_orders.csv docs/runbook-with-screenshots.md notebooks/retail_orders_pipeline.py sql/quality_checks.sql ``` Screenshot to save: ```text docs/screenshots/05-project-folder.png ``` ![Step 05 project folder](screenshots/05-project-folder.png) ## Step 06: Upload The CSV Option A, Unity Catalog volume: ```powershell databricks fs cp data/retail_orders.csv dbfs:/Volumes/main/default/demo/retail_orders.csv --overwrite ``` Option B, DBFS fallback: ```powershell databricks fs cp data/retail_orders.csv dbfs:/FileStore/databricks-retail-pipeline/retail_orders.csv --overwrite ``` Expected result: ```text File upload completes without error. ``` Screenshot to save: ```text docs/screenshots/06-upload-csv.png ``` ![Step 06 upload CSV](screenshots/06-upload-csv.png) ## Step 07: Validate The Bundle From `databricks-retail-pipeline/`: ```powershell databricks bundle validate ``` Expected result: ```text Validation OK! ``` Screenshot to save: ```text docs/screenshots/07-bundle-validate.png ``` ![Step 07 bundle validate](screenshots/07-bundle-validate.png) ## Step 08: Deploy The Bundle From `databricks-retail-pipeline/`: ```powershell databricks bundle deploy ``` Expected result: ```text Deployment completes and creates/updates the retail-orders-pipeline job. ``` Screenshot to save: ```text docs/screenshots/08-bundle-deploy.png ``` ![Step 08 bundle deploy](screenshots/08-bundle-deploy.png) ## Step 09: Run The Job From `databricks-retail-pipeline/`: ```powershell databricks bundle run retail_orders_pipeline ``` Expected result: ```text The job run starts and completes successfully. ``` Screenshot to save: ```text docs/screenshots/09-job-run.png ``` ![Step 09 job run](screenshots/09-job-run.png) Also capture the Databricks workspace job run page if possible. ## Step 10: Confirm Delta Tables In Databricks Catalog Explorer, open the target catalog and schema. Expected tables: ```text main.default.retail_clean_orders main.default.retail_daily_metrics main.default.retail_customer_metrics ``` Screenshot to save: ```text docs/screenshots/10-delta-tables.png ``` ![Step 10 Delta tables](screenshots/10-delta-tables.png) ## Step 11: Run Quality Checks Open a Databricks SQL editor and run: ```sql -- sql/quality_checks.sql ``` Expected result: - duplicate order check returns zero rows - null required field counts are zero - invalid financial value counts are zero - revenue and customer summary queries return rows Screenshot to save: ```text docs/screenshots/11-quality-checks.png ``` ![Step 11 quality checks](screenshots/11-quality-checks.png) ## Final Evidence To Keep When the project is complete, keep these artifacts together: ```text databricks-retail-pipeline/README.md databricks-retail-pipeline/databricks.yml databricks-retail-pipeline/notebooks/retail_orders_pipeline.py databricks-retail-pipeline/sql/quality_checks.sql databricks-retail-pipeline/docs/runbook-with-screenshots.md databricks-retail-pipeline/docs/screenshots/*.png ``` This gives you both a runnable Databricks project and a visual record of the implementation steps.