Merge branch 'current' into auth0-migration

vir108 · May 4, 2023 · 67dfea4 · 67dfea4
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diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
@@ -21,5 +21,5 @@ Adding new pages (delete if not applicable):
 
 Removing or renaming existing pages (delete if not applicable):
 - [ ] Remove page from `website/sidebars.js`
-- [ ] Add an entry `_redirects`
+- [ ] Add an entry `website/static/_redirects`
 - [ ] [Ran link testing](https://github.com/dbt-labs/docs.getdbt.com#running-the-cypress-tests-locally) to update the links that point to the deleted page
diff --git a/contributing/operating-model/outline.md b/contributing/operating-model/outline.md
@@ -0,0 +1,58 @@
+## Summary
+
+The operating model clarifies how to work with us and shows how we function, and increases our visibility and awareness. Here’s an outline that we can outline at Write the Docs in Portland 2023. (Our very first team offsite!)
+
+## What do we want to accomplish?
+
+1. Our Why? Define our strategy. Clearly define the goals that will drive the rest of the planning process. This is our mission statement, our voice and tone, and our statement of purpose.
+2. How we work. Tease out the internal team parts of our operating model. This part translates strategic intent into operational capabilities. Provides a foundation for action, and a clear guide for those who join our team, but also a window for others to better understand us. Includes who we are, our culture, our stakeholders.
+3. How to work with us. Define our external facing operations and processes. This will provide a clear guide for other teams so they understand what is expected of them, adn what to expect of us. Examples might take shape as: Process Maps, procedures, guidelines, work instructions, standards, tools, and more.
+
+## Shaping our **Operating model**
+
+### Strategy
+
+- [Style guide](https://github.com/dbt-labs/docs.getdbt.com/blob/current/contributing/content-style-guide.md)
+- Contribution guidelines
+- Voice & tone
+    _What is our Voice & Tone?_ 
+
+    > From the Community: Stick with it and, soon enough, you'll be able to harness the full power of dbt to achieve your data goals. Stay persistent, stay positive, and (most importantly) believe in yourself. You've got this!
+    > 
+    
+    > 💡Gentle and wise, but also reassuring and positive.
+    > 
+
+### People
+
+- **Team structure:** What roles do we all have and who should you ask what? We are OSS maintainers as well as a Docs team
+- **Culture:** Who are we and how do we conduct ourselves?
+- **Key stakeholders:** Internal or external customers include OS community, dbt Community, Townies (PMs, partnerships, revenue, SAs, Customer success, Training)
+
+### Processes
+
+- **Important processes we use to** perform our work, reviewing PRs (Townie and Community). Ideas for docs:
+
+    How we work:
+
+    - How we prioritize our work
+    - How do we work in the docs repo and dbt community slack? (I feel like we should have a general understanding of what work we do in the repo and slack)?
+
+    How to work with us:
+
+    - How to request help from Docs  / open an issue in GitHub. Great [data team example](https://www.notion.so/0dcd2d1375274ce9bfac609f3a4a8f6d) here!
+    - How to communicate with community prod docs team
+    - How to learn the style guide
+    - How do we work with other closely related teams like Developer experience? (Who to reach out to for what?)
+- **Communication:** What is our SLA (48hours?), how we handle Slack channels, what to ask in Slack vs GitHub issues vs Docs team projects, Docs Office hours (when we’re ready)
+- **Information we produce and consume**: Systems that we use to do our work, where is it stored, how can you contribute to it?
+
+### Data
+
+- Key **quantitative** metrics that we use to measure success.
+- Key **qualitative** metrics that we use to measure success and make decisions.
+
+### Tech/product
+
+- Technology: Where do we work and what are the systems in which we work?
+- Product: How does state of the product and changes to the product affect our team?
diff --git a/website/Makefile b/website/Makefile
diff --git a/website/blog/2021-10-15-october-21-product-update-email.md b/website/blog/2021-10-15-october-21-product-update-email.md
@@ -1,6 +1,6 @@
 ---
 title: "October 2021 dbt Update: Metrics and Hat Tricks 🎩"
-description: "Also flagging that Coalesce is less than 3 weeks away! 😱"
+description: "Stay up-to-date with the latest features in dbt. Read about our October 2021 product update."
 slug: dbt-product-update-2021-october
 authors: [lauren_craigie]
 

diff --git a/website/blog/2021-11-15-november-21-product-email.md b/website/blog/2021-11-15-november-21-product-email.md
@@ -1,6 +1,6 @@
 ---
 title: "November 2021 dbt Update: v1.0, Environment Variables, and a Question About the Size of Waves 🌊"
-description: "Also flagging that Coalesce is less than 3 weeks away! 😱"
+description: "Stay up-to-date with the latest features in dbt. Read about our November 2021 product update."
 slug: dbt-product-update-2021-november
 authors: [lauren_craigie] 
 

diff --git a/website/blog/2023-01-27-autoscaling-ci.md b/website/blog/2023-01-27-autoscaling-ci.md
@@ -12,6 +12,10 @@ date: 2023-01-25
 is_featured: true
 ---
 
+:::warning Deprecation Notice:  Update 4/27/2023
+dbt Cloud is now offering concurrent CI checks and auto cancellation of stale CI jobs as a native feature of the platform.  If you're interested, use [this form](https://docs.google.com/forms/d/e/1FAIpQLSfjSIMkwcwhZ7pbxT5ouuEf7dwpzUwRoGYBCjQApJ2ssps0tg/viewform) to sign up for our beta.
+:::
+
 Before I delve into what makes this particular solution "intelligent", let me back up and introduce CI, or continuous integration. CI is a software development practice that ensures we automatically test our code prior to merging into another branch. The idea being that we can mitigate the times when something bad happens in production, which is something that I'm sure we can all resonate with!
 
 <!--truncate-->

diff --git a/website/blog/2023-04-18-building-a-kimball-dimensional-model-with-dbt.md b/website/blog/2023-04-18-building-a-kimball-dimensional-model-with-dbt.md
@@ -16,7 +16,7 @@ is_featured: true
 
 <Lightbox src="/img/blog/2023-04-18-building-a-kimball-dimensional-model-with-dbt/data-modelling.png" width="85%" title="Data modeling techniques on a normalization vs denormalization scale"/>
 
-While the relevancy of dimensional modeling [has been debated by data practitioners](https://discourse.getdbt.com/t/is-kimball-dimensional-modeling-still-relevant-in-a-modern-data-warehouse/225/6), it is still one of the most widely adopted data modeling technique for analytics. 
+While the relevance of dimensional modeling [has been debated by data practitioners](https://discourse.getdbt.com/t/is-kimball-dimensional-modeling-still-relevant-in-a-modern-data-warehouse/225/6), it is still one of the most widely adopted data modeling technique for analytics.
 
 Despite its popularity, resources on how to create dimensional models using dbt remain scarce and lack detail. This tutorial aims to solve this by providing the definitive guide to dimensional modeling with dbt. 
 
@@ -513,7 +513,7 @@ inner join stg_salesorderheader on stg_salesorderdetail.salesorderid = stg_sales
 
 ### Step 5:  Select fact table columns
 
-You can now select the fact table columns that will help us answer the business questions identified earlier. We want to be able to calculate the amount of revenue, and therefore we include a column revenue per sales order detail which is calculated by `unitprice * orderqty as revenue` . 
+You can now select the fact table columns that will help us answer the business questions identified earlier. We want to be able to calculate the amount of revenue, and therefore we include a column revenue per sales order detail which was calculated above by `unitprice * orderqty as revenue` . 
 
 ```sql
 ...
@@ -623,7 +623,7 @@ The ERD will enable consumers of our dimensional model to quickly identify the k
 
 ## Part 7: Consume dimensional model
 
-Finally, we can consume our dimensional model by connecting to our data warehouse to our Business Intelligence (BI) tools such as Tableau, Power BI, and Looker. 
+Finally, we can consume our dimensional model by connecting our data warehouse to our Business Intelligence (BI) tools such as Tableau, Power BI, and Looker.
 
 Most modern BI tools have a built-in semantic layer that supports relationships between tables, which is required if we want to consume the dimensional models directly without any additional data transformation.