From 56c26a651643e79e0de204850a3e9b130cb48a55 Mon Sep 17 00:00:00 2001
From: royendo <67675319+royendo@users.noreply.github.com>
Date: Fri, 1 Aug 2025 13:09:31 -0600
Subject: [PATCH 1/3] new guides
---
docs/docs/guides/ga4-guide.md | 213 ++++++++++++++++++
docs/docs/guides/large-local-file.md | 10 +
.../guides/rill-clickhouse/r_ch_ingest.md | 2 +-
.../guides/rill-motherduck/1-r_md_launch.md | 48 ++++
.../guides/rill-motherduck/2-r_md_connect.md | 140 ++++++++++++
.../rill-motherduck/3-r_md_metrics-view.md | 63 ++++++
.../rill-motherduck/4-r_md_dashboard.md | 39 ++++
.../guides/rill-motherduck/5-r_md_deploy.md | 42 ++++
.../guides/rill-motherduck/_category_.yml | 6 +
docs/docs/guides/rill-motherduck/index.md | 25 ++
.../guides/rill-motherduck/r_ch_ingest.md | 99 ++++++++
docs/docs/guides/visualize-logging.md | 29 +++
12 files changed, 715 insertions(+), 1 deletion(-)
create mode 100644 docs/docs/guides/ga4-guide.md
create mode 100644 docs/docs/guides/large-local-file.md
create mode 100644 docs/docs/guides/rill-motherduck/1-r_md_launch.md
create mode 100644 docs/docs/guides/rill-motherduck/2-r_md_connect.md
create mode 100644 docs/docs/guides/rill-motherduck/3-r_md_metrics-view.md
create mode 100644 docs/docs/guides/rill-motherduck/4-r_md_dashboard.md
create mode 100644 docs/docs/guides/rill-motherduck/5-r_md_deploy.md
create mode 100644 docs/docs/guides/rill-motherduck/_category_.yml
create mode 100644 docs/docs/guides/rill-motherduck/index.md
create mode 100644 docs/docs/guides/rill-motherduck/r_ch_ingest.md
create mode 100644 docs/docs/guides/visualize-logging.md
diff --git a/docs/docs/guides/ga4-guide.md b/docs/docs/guides/ga4-guide.md
new file mode 100644
index 00000000000..045f6871b46
--- /dev/null
+++ b/docs/docs/guides/ga4-guide.md
@@ -0,0 +1,213 @@
+---
+title: "Google Analytics Guide"
+sidebar_label: "Google Analytics (GA4) Demo"
+sidebar_position: 5
+tags:
+ - Tutorial
+ - Quickstart
+ - Example Project
+---
+
+# Google Analytics (GA4) Demo Guide
+
+Rill makes it easy to visualize your GA4 data, empowering you to explore trends in website activity and make data-driven decisions with flexible, interactive analysis.
+
+:::note prerequisites
+Before you begin, ensure you have:
+- [Exported your GA4 data to BigQuery](https://support.google.com/analytics/answer/9823238?hl=en#step2&zippy=%2Cin-this-article)
+- [A service account key with access to BigQuery](https://cloud.google.com/bigquery/docs/use-service-accounts)
+
+You can explore the dataset directly in BigQuery:
+[GA4 Sample Dataset on BigQuery](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=ga4_obfuscated_sample_ecommerce&t=events_20210131&page=table&ref=ga4bigquery.com&inv=1&invt=Ab3HlA&project=rilldata)
+:::
+
+## Introduction
+
+This guide will walk you through each step, from ingesting your GA4 data to building and exploring interactive dashboards in Rill.
+
+---
+
+## Step 1: Ingest Data
+
+
+
+
+Start by connecting to your GA4 data source. For this guide, we’ll use Google’s public GA4 dataset, which is available in BigQuery.
+
+:::note Static Data
+The data provided by Google is a static dataset with data from November 2020 to 2021.
+:::
+
+
+
+
+When selecting BigQuery, Rill will prompt for:
+```
+`SQL` : select * from project_id.dataset.table; #select * from `bigquery-public-data.ga4_obfuscated_sample_ecommerce.events_20210131`
+`project_id`: your google console project_id
+`name`: name of source in Rill
+```
+
+### Partitioned GA4 Data
+
+
+
+
+If you are following along with this guide, use the following public dataset:
+
+- **Project:** `bigquery-public-data`
+- **Dataset:** `ga4_obfuscated_sample_ecommerce`
+- **Table prefix:** `events_*`
+
+If you are using your own data, you can make use of GA4's partitioned data using the `__TABLE_SUFFIX` parameter.
+
+
+
+
+---
+
+## Step 2: Expand the Columns
+
+After connecting your data, you may want to expand nested columns or flatten the event structure for easier analysis by creating a model.
+
+
+
+
+:::tip Rill's Default Embedded Database, DuckDB
+By default, Rill uses DuckDB as its underlying embedded database. This means that for any modeling, this will be done in DuckDB SQL.
+:::
+
+
+
+
+
+Sample Model SQL
+
+```SQL
+SELECT
+ event_date,
+ user_pseudo_id,
+ to_timestamp(event_timestamp/ 1000000) as event_timestamp, -- convert 1608921004450512 to a proper timestamp
+ to_timestamp(user_first_touch_timestamp / 1000000) as user_first_touch_timestamp, --convert 1608921004450512 to timestamp, used to count time of session later
+
+ stream_id,
+ platform,
+ event_name,
+ event_value_in_usd,
+ event_bundle_sequence_id,
+
+ -- privacy_info
+ -- json_extract(main.privacy_info, '$.ads_storage')::VARCHAR AS priv_info_ads_storage,
+ -- json_extract(main.privacy_info, '$.analytics_storage')::VARCHAR AS priv_info_analytics_storage,
+ -- json_extract(main.privacy_info, '$.uses_transient_token')::VARCHAR AS priv_info_uses_transient_token,
+
+ -- user_ltv
+ json_extract(main.user_ltv, '$.currency')::VARCHAR AS ltv_currency,
+ CAST(json_extract(main.user_ltv, '$.revenue') AS DOUBLE) AS ltv_revenue,
+
+ -- device
+ -- json_extract(main.device, '$.advertising_id')::VARCHAR AS device_advertising_id,
+ json_extract(main.device, '$.category')::VARCHAR AS device_category,
+ -- json_extract(main.device, '$.is_limited_ad_tracking')::VARCHAR AS device_is_limited_ad_tracking,
+ json_extract(main.device, '$.language')::VARCHAR AS device_language,
+ json_extract(main.device, '$.mobile_brand_name')::VARCHAR AS device_mobile_brand_name,
+ -- json_extract(main.device, '$.mobile_marketing_name')::VARCHAR AS device_mobile_marketing_name,
+ json_extract(main.device, '$.mobile_model_name')::VARCHAR AS device_mobile_model_name,
+ -- json_extract(main.device, '$.mobile_os_hardware_model')::VARCHAR AS device_mobile_os_hardware_model,
+ json_extract(main.device, '$.operating_system')::VARCHAR AS device_operating_system,
+ json_extract(main.device, '$.operating_system_version')::VARCHAR AS device_operating_system_version,
+ -- CAST(json_extract(main.device, '$.time_zone_offset_seconds') AS INT) AS device_time_zone_offset_seconds,
+ -- json_extract(main.device, '$.vendor_id')::VARCHAR AS device_vendor_id,
+ json_extract(main.device, '$.web_info.browser')::VARCHAR AS device_browser,
+ json_extract(main.device, '$.web_info.browser_version')::VARCHAR AS device_browser_version,
+
+ -- geo
+ json_extract(main.geo, '$.city')::VARCHAR AS geo_city,
+ json_extract(main.geo, '$.continent')::VARCHAR AS geo_continent,
+ json_extract(main.geo, '$.country')::VARCHAR AS geo_country,
+ -- json_extract(main.geo, '$.metro')::VARCHAR AS geo_metro,
+ json_extract(main.geo, '$.region')::VARCHAR AS geo_region,
+ json_extract(main.geo, '$.sub_continent')::VARCHAR AS geo_sub_continent,
+
+ -- traffic_source
+ json_extract(main.traffic_source, '$.medium')::VARCHAR AS traffic_medium,
+ json_extract(main.traffic_source, '$.name')::VARCHAR AS traffic_name,
+ json_extract(main.traffic_source, '$.source')::VARCHAR AS traffic_source,
+
+ -- ecommerce
+ CAST(json_extract(main.ecommerce, '$.purchase_revenue') AS DOUBLE) AS ecommerce_purchase_revenue,
+ CAST(json_extract(main.ecommerce, '$.purchase_revenue_in_usd') AS DOUBLE) AS ecommerce_purchase_revenue_in_usd,
+ CAST(json_extract(main.ecommerce, '$.refund_value') AS DOUBLE) AS ecommerce_refund_value,
+ CAST(json_extract(main.ecommerce, '$.refund_value_in_usd') AS DOUBLE) AS ecommerce_refund_value_in_usd,
+ CAST(json_extract(main.ecommerce, '$.shipping_value') AS DOUBLE) AS ecommerce_shipping_value,
+ CAST(json_extract(main.ecommerce, '$.shipping_value_in_usd') AS DOUBLE) AS ecommerce_shipping_value_in_usd,
+ CAST(json_extract(main.ecommerce, '$.tax_value') AS DOUBLE) AS ecommerce_tax_value,
+ CAST(json_extract(main.ecommerce, '$.tax_value_in_usd') AS DOUBLE) AS ecommerce_tax_value_in_usd,
+ -- CAST(json_extract(main.ecommerce, '$.total_item_quantity') AS INT) AS ecommerce_total_item_quantity,
+ json_extract(main.ecommerce, '$.transaction_id')::VARCHAR AS ecommerce_transaction_id,
+ -- CAST(json_extract(main.ecommerce, '$.unique_items') AS INT) AS ecommerce_unique_items,
+
+-- items (exploded)
+-- json_extract(item.value, '$.affiliation')::VARCHAR AS value_item_affiliation,
+-- json_extract(item.value, '$.coupon')::VARCHAR AS value_item_coupon,
+json_extract(item.value, '$.creative_name')::VARCHAR AS value_creative_name,
+-- json_extract(item.value, '$.creative_slot')::VARCHAR AS value_creative_slot,
+json_extract(item.value, '$.item_brand')::VARCHAR AS value_item_brand,
+json_extract(item.value, '$.item_category')::VARCHAR AS value_item_category,
+-- json_extract(item.value, '$.item_category2')::VARCHAR AS value_item_category2,
+-- json_extract(item.value, '$.item_category3')::VARCHAR AS value_item_category3,
+-- json_extract(item.value, '$.item_category4')::VARCHAR AS value_item_category4,
+-- json_extract(item.value, '$.item_category5')::VARCHAR AS value_item_category5,
+json_extract(item.value, '$.item_id')::VARCHAR AS value_item_id,
+-- json_extract(item.value, '$.item_list_id')::VARCHAR AS value_item_list_id,
+json_extract(item.value, '$.item_list_index')::VARCHAR AS value_item_list_index,
+json_extract(item.value, '$.item_list_name')::VARCHAR AS value_item_list_name,
+json_extract(item.value, '$.item_name')::VARCHAR AS value_item_name,
+CAST(json_extract(item.value, '$.item_refund') AS DOUBLE) AS value_item_refund,
+CAST(json_extract(item.value, '$.item_refund_in_usd') AS DOUBLE) AS value_item_refund_in_usd,
+CAST(json_extract(item.value, '$.item_revenue') AS DOUBLE) AS value_item_revenue,
+CAST(json_extract(item.value, '$.item_revenue_in_usd') AS DOUBLE) AS value_item_revenue_in_usd,
+json_extract(item.value, '$.item_variant')::VARCHAR AS value_item_variant,
+-- json_extract(item.value, '$.location_id')::VARCHAR AS value_location_id,
+CAST(json_extract(item.value, '$.price') AS DOUBLE) AS value_item_price,
+CAST(json_extract(item.value, '$.price_in_usd') AS DOUBLE) AS value_item_price_in_usd,
+-- json_extract(item.value, '$.promotion_id')::VARCHAR AS value_promotion_id,
+json_extract(item.value, '$.promotion_name')::VARCHAR AS value_promotion_name,
+-- CAST(json_extract(item.value, '$.quantity') AS INT) AS value_item_quantity
+
+FROM obfuscated_sample_ecommerce AS main,
+json_each(main.items) AS item
+```
+
+
+---
+
+## Step 3: Create a Metrics View
+
+With your data modeled, you can now define metrics and dimensions for analysis. In Rill, you have the option to create metrics via AI, which will send the schema and related information to OpenAI to build a basic metrics view. From there, you can make changes, add, or remove unneeded dimensions and measures.
+
+
+
+
+Leverage Rill’s AI-powered features to quickly generate metrics views tailored to your business questions.
+
+
+
+
+---
+
+## Step 4: Visualize Your Data
+
+Finally, explore your GA4 data with interactive dashboards and visualizations. Here are a few example analyses you can perform in Rill:
+
+- **Traffic Trends:** Track daily or weekly website sessions and identify spikes or drops in user activity.
+- **User Segmentation:** Break down users by country, device type, or traffic source to understand your audience.
+- **Ecommerce Performance:** Analyze purchase revenue, refund rates, and top-selling products over time.
+- **Event Analysis:** Visualize key events (like sign-ups or checkouts) to optimize conversion funnels.
+
+
+
+
+Use Rill’s dashboard to analyze trends, segment users, and uncover insights from your GA4 events.
+
+---
\ No newline at end of file
diff --git a/docs/docs/guides/large-local-file.md b/docs/docs/guides/large-local-file.md
new file mode 100644
index 00000000000..fed68514eff
--- /dev/null
+++ b/docs/docs/guides/large-local-file.md
@@ -0,0 +1,10 @@
+---
+title: Working with a Large File Locally
+sidebar_label: "Large Local File"
+hide_table_of_contents: false
+sidebar_position: 50
+
+tags:
+ - Quickstart
+ - Tutorial
+---
diff --git a/docs/docs/guides/rill-clickhouse/r_ch_ingest.md b/docs/docs/guides/rill-clickhouse/r_ch_ingest.md
index 4fe615eb2b0..bd9c0b0d842 100644
--- a/docs/docs/guides/rill-clickhouse/r_ch_ingest.md
+++ b/docs/docs/guides/rill-clickhouse/r_ch_ingest.md
@@ -1,7 +1,7 @@
---
title: "Ingesting Data into ClickHouse"
sidebar_label: "Ingesting Data Directly into ClickHouse"
-sidebar_position: 4
+sidebar_position: 40
hide_table_of_contents: false
tags:
- OLAP:ClickHouse
diff --git a/docs/docs/guides/rill-motherduck/1-r_md_launch.md b/docs/docs/guides/rill-motherduck/1-r_md_launch.md
new file mode 100644
index 00000000000..852f81462bd
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/1-r_md_launch.md
@@ -0,0 +1,48 @@
+---
+title: "1. Launch Rill Developer"
+sidebar_label: "1. Launch Rill Developer"
+sidebar_position: 3
+hide_table_of_contents: false
+tags:
+ - OLAP:ClickHouse
+ - Tutorial
+---
+
+:::note prerequisites
+You will need to [install Rill](https://docs.rilldata.com/home/install).
+
+```bash
+curl https://rill.sh | sh
+```
+
+You need access to either a [locally running ClickHouse Server](https://clickhouse.com/docs/en/install) or [ClickHouse Cloud](https://docs.rilldata.com/reference/olap-engines/clickhouse#connecting-to-clickhouse-cloud). We recommend using ClickHouse Cloud as this will make deploying to Rill Cloud easier. Please review the documentation, [here](https://docs.rilldata.com/reference/olap-engines/clickhouse).
+:::
+## Start Rill Developer
+
+```yaml
+rill start my-rill-clickhouse
+```
+
+After running the command, Rill Developer should automatically open in your default browser. If not, you can access it via the following url:
+
+```
+localhost:9009
+```
+
+You should see the following webpage appear.
+
+
+
+
+Let's go ahead and select `Start with an empty project`.
+
+
+ Where am I in the terminal?
+
+ You can use the `pwd` command to see which directory in the terminal you are.
+ If this is not where you'd like to make the directory use the `cd` command to change directories.
+
+
+
+
+
diff --git a/docs/docs/guides/rill-motherduck/2-r_md_connect.md b/docs/docs/guides/rill-motherduck/2-r_md_connect.md
new file mode 100644
index 00000000000..283fc7e446a
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/2-r_md_connect.md
@@ -0,0 +1,140 @@
+---
+title: "2. Connect to MotherDuck"
+sidebar_label: "2. Connect to MotherDuck"
+sidebar_position: 3
+hide_table_of_contents: false
+tags:
+ - OLAP:MotherDuck
+ - Tutorial
+---
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+
+## Default OLAP connection and Connect to MotherDuck
+
+Within Rill you can set the default OLAP connection on the [project level](https://docs.rilldata.com/reference/project-files/rill-yaml) or the [dashboard level](https://docs.rilldata.com/reference/project-files/explore-dashboards).
+For this course, we will set it up on the project level so all of our dashboards will be based on our MotherDuck table.
+
+:::tip
+You have two options for your MotherDuck server:
+1. Use a [local running MotherDuck server](https://MotherDuck.com/docs/en/install)
+2. Use [MotherDuck Cloud](https://MotherDuck.com/docs/en/cloud/overview)
+
+Depending what you choose, the contents of your connection will change and I recommend looking through [our MotherDuck documentation](https://docs.rilldata.com/reference/olap-engines/MotherDuck) for further information.
+
+:::
+
+### Connect to MotherDuck
+We can create the MotherDuck connection by selection `+Add Data` > `MotherDuck` and fill in the components on the UI.
+
+
+
+:::tip
+You can obtain the credentials from your MotherDuck Cloud account by clicking the `Connect` button in the left panel.:
+
+
+
+```
+"https://:?username=&password=&secure=true&skip_verify=true"
+```
+
+:::
+Once this is created, a `MotherDuck.yaml` file will appear in the `connectors` folder and the following will be added to your rill.yaml.
+
+```yaml
+compiler: rillv1
+
+title: "Rill and MotherDuck Project"
+olap_connector: MotherDuck #automatically added
+```
+
+Example for a locally running MotherDuck server:
+```yaml
+host: "localhost"
+port: "9000"
+```
+or
+```yaml
+dsn: "MotherDuck://localhost:9000"
+```
+
+
+ You can either add the credentials in plain text or dsn via the yaml file or add the credentials via the CLI.
+
+
+Please see our documentation to find the DSN for [your MotherDuck Cloud instance](https://docs.rilldata.com/reference/olap-engines/MotherDuck#connecting-to-MotherDuck-cloud).
+
+### How to pass the credentials to Rill
+There are a few way to define the credentials within Rill.
+
+
+
+Please create a file called MotherDuck.yaml and add the following contents.
+```yaml
+type: connector
+driver: MotherDuck
+
+host: "localhost"
+port: "9000"
+```
+or
+```yaml
+type: connector
+driver: MotherDuck
+
+dsn: "MotherDuck://localhost:9000"
+```
+
+
+
+
+
+Navigate back to the Terminal and stop the Rill process. You can run the following to add a variable and use this is within Rill.
+
+```
+rill start --env host='localhost' --env port='9000'
+```
+
+Afterwards, create a file called MotherDuck.yaml and add the following contents:
+
+```yaml
+type: connector
+driver: MotherDuck
+
+host: '{{ .env.host }}'
+port: '{{ .env.port }}'
+```
+
+
+
+
+
+
+
+There's a few way to generate the .env file. Making a source that requires credentials will automatically generate it. Else, you can create it using `touch .env` in the rill directory.
+
+```yaml
+connector.MotherDuck.host="localhost"
+connector.MotherDuck.port=9000
+connector.MotherDuck.username
+connector.MotherDuck.password
+connector.MotherDuck.ssl
+
+or
+
+connector.MotherDuck.dsn="..."
+```
+
+
+
+
+:::tip Via the UI
+
+If you connect to MotherDuck via the UI, this will automatically create a template with connectors/MotherDuck.yaml as well as a reference of your DSN to the .env folder. This will automatically get pushed along with your project to Rill Cloud.
+
+:::
+
+You should now be able to see the contents of your MotherDuck database in the left panel of your UI.
+
+
diff --git a/docs/docs/guides/rill-motherduck/3-r_md_metrics-view.md b/docs/docs/guides/rill-motherduck/3-r_md_metrics-view.md
new file mode 100644
index 00000000000..5baa342929f
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/3-r_md_metrics-view.md
@@ -0,0 +1,63 @@
+---
+title: "3. Create Metrics View Dashboard in Rill"
+sidebar_label: "3. Create Metrics View Dashboard in Rill"
+sidebar_position: 3
+hide_table_of_contents: false
+tags:
+ - OLAP:MotherDuck
+ - Tutorial
+---
+
+## Create the Metrics View.
+
+If you noticed in the previous screenshot, we had a table called `uk_price_paid`. This is a dataset that is used in MotherDuck's Learning portal, so we thought it was fitting to go ahead and continue on this dataset.
+
+:::note
+In the case that you have not already added this table to your local or Cloud database, please follow the steps on [MotherDuck's site](https://MotherDuck.com/docs/en/getting-started/example-datasets/uk-price-paid) for the steps to do so!
+:::
+
+### Create metrics view
+
+Let's create a metrics view based on the table via the `Generate metrics via AI`.
+
+
+
+
+### What are we looking at?
+
+This is our metrics view, where we can define measures and dimensions to be used on dashboards.
+
+```yaml
+# Metrics view YAML
+# Reference documentation: https://docs.rilldata.com/reference/project-files/explore-dashboards
+# This file was generated using AI.
+
+version: 1
+type: metrics_view
+
+title: UK Price Paid Metrics
+connector: MotherDuck
+table: uk_price_paid
+timeseries: date
+
+dimensions:
+ ...
+
+measures:
+ ...
+```
+
+
+
+
+While we go into more details in our [Rill Basics course](/guides/rill-basics/dashboard) and [our documentation](https://docs.rilldata.com/build/dashboards/), let's go over it quickly.
+
+---
+
+`timeseries` - This is our time column that is used on as our x-axis for graphs.
+
+`connector` - this is our manually defined MotherDuck connector
+
+`dimensions` - These are our categorical columns that we can use on the dashboard to filter and slice;
+
+`measures` - These are our numerical aggregates defined in the metrics layer. We can see functions such as MAX(), COUNT(), and AVG() used on the underlying table.
\ No newline at end of file
diff --git a/docs/docs/guides/rill-motherduck/4-r_md_dashboard.md b/docs/docs/guides/rill-motherduck/4-r_md_dashboard.md
new file mode 100644
index 00000000000..b3e0278d0a9
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/4-r_md_dashboard.md
@@ -0,0 +1,39 @@
+---
+title: "4. Create Explore Dashboard in Rill"
+sidebar_label: "4. Create Explore Dashboard in Rill"
+sidebar_position: 4
+hide_table_of_contents: false
+tags:
+ - OLAP:MotherDuck
+ - Tutorial
+---
+
+
+### Create the explore dashboard
+
+When you're ready, you can create the visualization on top of the metric layer. Let's select `Create Explore dashboard`. This will create a simple explore-dashboards/uk_price_paid_metrics_explore.yaml file that reads in all the dimensions and measures. For more information on the available key-pairs, please refer to the [reference documentation.](https://docs.rilldata.com/reference/project-files/explore-dashboards)
+
+---
+
+### What can we do in Rill?
+In our case, as we have generated this with AI, so we can look through the description of the populated measures for more information. Based on this, we can find some specific information on the UK properties dataset at a glance, such as:
+
+1. In 2023, What was the minimum/maximum detached property sold in London? [46.5K, 65.0M]
+2. In 2023, What was the average price of detached properties sold in London? How many? [2.5M, 981]
+
+
+
+
+
+If we wanted to go further into details, we can even compare detached vs flat vs terraced properties using our compare feature. Based on the x-axis, we can drill down futher from the 2023 year into a specific month, week, or even day.
+
+
+
+
+
+Or, if you want to compare time periods 2022 to 2023's total transactions. In the below screenshot, we selected the Total Transactions metric and enable the time-compare feature to see the delta, delta percent of change from two time periods.
+
+
+
+
+These are just a few examples of what we can do with Rill, the options expand further and are discussed further in [Rill Advanced](https://docs.rilldata.com/tutorials/rill_learn_200/201_0). If you're interested I recommended reviewing the contents after finishing up this course.
\ No newline at end of file
diff --git a/docs/docs/guides/rill-motherduck/5-r_md_deploy.md b/docs/docs/guides/rill-motherduck/5-r_md_deploy.md
new file mode 100644
index 00000000000..69f11887872
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/5-r_md_deploy.md
@@ -0,0 +1,42 @@
+---
+title: "5. Deploy to Rill Cloud"
+sidebar_label: '5. Deploy to Rill Cloud'
+sidebar_position: 9
+hide_table_of_contents: false
+tags:
+ - OLAP:MotherDuck
+ - Tutorial
+---
+:::tip Rill Cloud Trial
+
+If this is the first time you have deployed a project onto Rill Cloud, you will automatically start your [Rill Cloud Trial] () upon deployment of your Rill project. Your trial will last for 30 days. Please refer [here] () for more information on the details of your trial.
+
+:::
+
+## Deploy via the UI!
+
+Select the `Deploy to share` button in the top right corner of a dashboard.
+
+
+
+
+Steps to deploy to Rill Cloud:
+1. Select the `Deploy to share` button.
+2. Select `continue` on the free trial [link to article of free trial explanation]
+ - If you have multiple organizations, please select Rill_Learn and `continue`.
+3. Select `continue` on user invites.
+4. You will be navigated to the /status page of your deployed project.
+
+
+Take note of the following features in the UI:
+
+
+## In case of the following error:
+
+```bash
+connection: dial tcp 127.0.0.1:9000: connect: connection refused
+```
+
+This is likely due to using a locally running MotherDuck server. If so, you will not be able to access your locally running server from Rill Cloud. Instead, we suggest using [MotherDuck Cloud](https://MotherDuck.com/cloud).
+
+For steps to setup MotherDuck Cloud, please refer to [our documentation](https://docs.rilldata.com/reference/olap-engines/MotherDuck#connecting-to-MotherDuck-cloud).
diff --git a/docs/docs/guides/rill-motherduck/_category_.yml b/docs/docs/guides/rill-motherduck/_category_.yml
new file mode 100644
index 00000000000..537289d5e1a
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/_category_.yml
@@ -0,0 +1,6 @@
+position: 02
+label: "Visualize your MotherDuck Tables in Rill"
+collapsible: true
+collapsed: true
+
+
diff --git a/docs/docs/guides/rill-motherduck/index.md b/docs/docs/guides/rill-motherduck/index.md
new file mode 100644
index 00000000000..fe7f7f9a662
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/index.md
@@ -0,0 +1,25 @@
+---
+title: Visualize your MotherDuck Tables in Rill!
+description: tutorial for MotherDuck
+sidebar_position: 3
+tags:
+ - Tutorial
+ - OLAP:MotherDuck
+---
+
+
+
+
+
+In this tutorial, we will discuss how to use MotherDuck as the default OLAP database with Rill to visualize your MotherDuck tables in as little as a few clicks.
+
+The overall steps of the tutorial are:
+1. Launch Rill Developer
+2. Connect to your MotherDuck server whether it is locally run or via MotherDuck Cloud
+3. Create a metrics view based on a table in MotherDuck
+4. Create an explore dashboard via Generative AI
+5. Deploy the dashboard to Rill Cloud, and share to colleagues
+
+Once completed, you will have a basic understanding of how to use Rill Developer with MotherDuck and can customize the Rill Developer project to create further metrics views based on MotherDuck tables and create more dashboards.
+
+### Let's get started!
\ No newline at end of file
diff --git a/docs/docs/guides/rill-motherduck/r_ch_ingest.md b/docs/docs/guides/rill-motherduck/r_ch_ingest.md
new file mode 100644
index 00000000000..4029c87a0ef
--- /dev/null
+++ b/docs/docs/guides/rill-motherduck/r_ch_ingest.md
@@ -0,0 +1,99 @@
+---
+title: "Ingesting Data into MotherDuck"
+sidebar_label: "Ingesting Data Directly into MotherDuck"
+sidebar_position: 40
+hide_table_of_contents: false
+tags:
+ - OLAP:MotherDuck
+ - Tutorial
+---
+
+## Importing your own Data into MotherDuck from ...
+
+Currently, MotherDuck lacks some [direct ingestion](https://MotherDuck.com/docs/en/migrations/snowflake) from certain providers. You can navigate to their website for a full list of data sources in which they support [direct ingestion](https://MotherDuck.com/docs/en/integrations), via manual import or [ClickPipes](https://MotherDuck.com/cloud/clickpipes).
+
+### How does this affect Rill?
+
+When switching from DuckDB, you may have noticed some changes to the capabilities of Rill. By default, we disable modeling when MotherDuck is enabled as the default OLAP engine. However, we can change this behavior by enabling the feature flag `MotherDuckModeling`.
+
+```yaml
+features:
+ MotherDuckModeling: true
+ ```
+
+Once this is enabled, you'll be able to create model files and add sources in the UI and use these for SQL transformations, as you would with DuckDB.
+
+:::note
+Currently not all the functionality is supported but our team is working on this to add more features! Please reach out to us on our community or via GitHub for any specific missing functionality that you looking for.
+:::
+
+## Ingestion directly from Snowflake to MotherDuck
+
+In the below example, we are importing data from Snowflake to MotherDuck using S3 as an intermediate stage.
+```yaml
+type: model
+materialize: true
+
+-- the source of data in Snowflake
+connector: snowflake
+sql: >
+ select * from CUSTOMER limit 1001
+
+-- the staging table in S3
+stage:
+ connector: s3
+ path: s3://rill-developer.rilldata.io/snow
+
+-- the output MotherDuck connector
+output:
+ connector: MotherDuck
+ materialize: true
+```
+
+In order to use this method you will need to set your credentials in .env. If the .env does not already exist (it will be created by default if you have created a source), you can create a .env file in the rill directory by running `touch .env` and this should now be visible in Rill Developer.
+
+```
+connector.MotherDuck.host="localhost"
+connector.MotherDuck.port=9000
+connector.snowflake.dsn=""
+connector.s3.aws_access_key_id=""
+connector.s3.aws_secret_access_key=""
+```
+:::note
+If you already set up MotherDuck via the .env file, you will just need to add your snowflake and s3 credentials.
+:::
+
+
+## Ingestion directly from BigQuery to MotherDuck
+
+In the below example, we are importing data from Big Query directly to MotherDuck using GCS as an intermediate stage.
+
+
+```yaml
+type: model
+materialize: true
+
+connector: bigquery
+sql: |
+ SELECT
+ *
+ FROM `..`
+
+project_id: ""
+
+stage:
+ connector: gcs
+ path: 'gs://rill-bq-ch/temp/'
+
+
+output:
+ connector: MotherDuck
+```
+
+You'll need to ensure that your provided `google_application_credentials` have all the required permissions on both [BigQuery](https://cloud.google.com/bigquery/docs/access-control) and [GCS](https://cloud.google.com/storage/docs/access-control/iam-roles). Ensure that your .env has the following:
+
+```
+connector.MotherDuck.host="localhost"
+connector.MotherDuck.port=9000
+google_application_credentials=""
+```
\ No newline at end of file
diff --git a/docs/docs/guides/visualize-logging.md b/docs/docs/guides/visualize-logging.md
new file mode 100644
index 00000000000..8f9794049d3
--- /dev/null
+++ b/docs/docs/guides/visualize-logging.md
@@ -0,0 +1,29 @@
+---
+title: "Visualize your Logging Data"
+sidebar_label: "Visualize Logging Data Demo"
+sidebar_position: 10
+hide_table_of_contents: false
+tags:
+ - Tutorial
+ - Quickstart
+ - Example Project
+---
+
+## Introduction
+
+There are many different types of CDN, logging systems blah blah
+
+### Requirements for Rill (embedded DuckDB) vs. Using ClickHouse (Clickpipes)
+Pros and Cons
+
+
+## Setting up the data pipeline (in Rill) or skip if you've already have this is ClickHouse table
+
+## Exploring the Data in Rill
+
+## Creating the metrics view
+
+## Visualize Data
+
+
+
From 2464fe8a8f99bf60465bfa5a07c37704a4e61709 Mon Sep 17 00:00:00 2001
From: royendo <67675319+royendo@users.noreply.github.com>
Date: Fri, 1 Aug 2025 13:28:35 -0600
Subject: [PATCH 2/3] screenshost
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