Merge pull request #137 from DataRecce/whyrecce

Updated overview page with improved introduction and 'why Recce' section

docs/docs/index.md

@@ -4,16 +4,94 @@ icon: material/hand-wave-outline
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-# Start your Data Reconnaissance Mission
+# What is `Recce`?
 
-## What is `Recce`?
+`Recce` is a data validation toolkit designed to enhance the pull request (PR) review process for dbt projects. `Recce` provides enhanced visibility into the data impact from dbt modeling changes by comparing the data in dev and prod environments. Using Recce for data impact assessment before merging a PR ensures that production data remains stable and accurate.
 
-`Recce` is a data-change validation tool for [dbt](https://www.getdbt.com/) projects. `Recce` provides a convenient platform to perform cross-environment diffs as data modeling validations. Use these validations in your pull request (PR) comment to demonstrate proof-of-correctness of your modeling changes and speed up thew QA process of PR review.
+## Key Features
+
+### Manual and Automated Data Checks
+
+`Recce` checks help you to assess data impact and explore data change both manually and automatically. 
+
+- **Manual checks** - Create a `Recce` <a href="https://medium.com/inthepipeline/build-a-checklist-for-better-dbt-pr-review-913906ff11dd" target="blank">Checklist</a> of data checks that help to validate your data modeling work during development, including data profile comparisons, structural comparisons, and row-level data checks.
+- **Automated checks** - Integrate `Recce` Checks into your CI process and post a data impact summary automatically to your PR thread when opening a PR.
+
+### Collaboration and Replication
+
+Share `Recce` checks with your team for stakeholder and PR review. Checks results can be either [shared individually](features/lineage.md#screenshot), or your full `Recce` <a href="https://medium.com/inthepipeline/enhanced-dbt-pr-review-with-reproducible-data-validation-environments-e6c37a15908f" target="_blank">environment can be exported</a> and [replicated with one command](features/state-file.md#review-the-state-file).
+
+
+## Why Recce
+
+dbt has brought software engineering best practices to data projects, but “bad merges” still happen, allowing erroneous data and silent errors to make their way into prod data.
+
+### Understand data impact
+
+`Recce` provides data and analytics engineers with a toolkit to explore data impact caused by dbt data modeling changes. The varying levels of `Recce` checks enable holistic or fine grained impact assessment so you can drill down to find the root cause of data change.
+
+### Improved confidence merging
+
+The improved visibility into data impact gives PR reviewers the confidence to sign-off PRs knowing that prod data will not change unexpectedly.
 
 
 <div style="position: relative; padding-bottom: 71.68758716875871%; height: 0;"><iframe src="https://www.loom.com/embed/f6ea8a9b37964cbd9821bb6896d3206f?sid=9c701279-08cd-45c5-b12d-e7967d8f898d" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
 
 
+## How `Recce` Works
+
+`Recce` compares dbt environments using the dbt artifacts from both `dev` and `prod` environments. 
+
+1. Generate artifacts for the `prod` environment:
+
+```
+# Build prod and generate dbt docs into ./target-base
+dbt seed --target prod
+dbt run --target prod
+dbt docs generate --target prod --target-path ./target-base
+```
+
+1. Switch to your `dev` branch and generate dev artifacts:
+
+```
+# Switch to your dev branch
+git switch my-awesome-branch
+
+# build your dev environment
+dbt seed
+dbt run
+dbt docs generate
+```
+
+1. Start your `Recce` Instance:
+
+```
+recce server
+```
+
+Open your the `Recce` web UI to start exploring and understanding data impact, and validating your work.
+
+## What you get
+
+### Interactive impact assessment environment
+
+`recce server` launches a web UI with an [**interactive impact assessment environment**](features/lineage.md). Use the tools in `Recce` to explore the impact to your data models from your branch changes.
+
+### Focused data impact exploration
+
+The main interface to `Recce` is the [lineage DAG](features/lineage.md#node-summary), which shows modified nodes and potentially impacted downstream nodes. You can quickly see if critical nodes are within the impact radius and focus your data validation efforts.
+
+
+<figure markdown>
+  ![Recce Lineage Diff](../assets/images/recce-ui-elements.png)
+  <figcaption>	</figcaption>
+</figure>
+
+## Getting Started
+
+Try the [5-minute tutorial](get-started-jaffle-shop.md) that uses dbt’s Jaffle Shop project, or take the [online demo](docs/demo.md) for a test run, which includes an actual PR and related Recce Instance.
+
+
+## What does `Recce` mean?
 
-## The definition of `Recce`
-`Recce` (/ˈrɛki/), pronounced 'reh-kee', is short for 'reconnaissance'. We chose this name as it's the perfect fit for a tool you'll use to perform data reconnaissance to discover and assess the impact of data modeling changes. Add a `Data Recce` to your pull request workflow and stop pushing breaking changes to production.
+`Recce` (/ˈrɛki/), pronounced 'reh-kee', is short for 'reconnaissance'. We chose this name as it's the perfect fit for a tool you'll use to perform a 'data reconnaissance' to discover and assess the impact of data modeling changes. Add a `Data Recce` to your pull request workflow and stop pushing breaking changes to production!