class: title, center, middle # Deploying your dbt project --- # We've built our first models... now what? -- - How will our team members access them? They are currently in a schema named `dbt_jdoe` -- - What happens when our underlying data gets updated? -- - What happens when we add new models, or change existing ones? --- # Solution: -- - Run dbt on a schedule - Use a "trusted" schema for this run Also known as: - Running dbt in production - Deploying your dbt project --- <!-- Template for displaying the focus slides for each presentation --> <h1>Deployment | Focus</h1> <li> Understand why you need to deploy a dbt project </li> <li> Consider the advantages of deploying a dbt project on a schedule </li> --- # dbt Cloud Deployment The scheduler in dbt Cloud is purpose built for running dbt jobs on a schedule. - ✅ Always pulls the latest version of your project - ✅ Easy to build on Pull Request (and tear down the schema afterwards) - ✅ Easy to generate and share documentation with users - ✅ Secure access model - ✅ Email and Slack notifications if something goes wrong, with rich logs - ✅ Persist run artifacts for later comparison and analysis --- <img src="/ui/img/dbt-learn/NOLA_live/deployment slide 6 (line 66).png" style="width: 100%;"> ??? - This is what your Home Dashboard will look like once you have jobs running in Production. - You'll see successes, errors, etc. and you can click through each invocation of a job for more information. --- # Resources * [Deploy with dbt Cloud](https://docs.getdbt.com/docs/deploy/deployments) * [Selection Syntax](https://docs.getdbt.com/reference/node-selection/syntax) * [Model Timing](https://docs.getdbt.com/docs/deploy/dbt-cloud-job#model-timing) * [Job Notifications](https://docs.getdbt.com/docs/deploy/job-notifications) --- class: subtitle #Zoom Out <li>dbt Learn Norms</li> <li>Why dbt?</li> <li>Modeling</li> <li>Project Design</li> <li>Testing</li> <li>Sources</li> <li>Docs</li> <li>Deployment</li>