Merge pull request ClickHouse#1916 from IstvanM/patch-1

docs: Adding Mitzu to integrations

docs/en/integrations/data-visualization.md

@@ -1,7 +1,7 @@
 ---
 sidebar_label: Overview
 sidebar_position: 1
-keywords: [clickhouse, connect, explo, tableau, grafana, metabase, superset, deepnote, draxlr, rocketbi, bi, visualization, tool]
+keywords: [clickhouse, connect, explo, tableau, grafana, metabase, mitzu, superset, deepnote, draxlr, rocketbi, bi, visualization, tool]
 ---
 
 # Visualizing Data in ClickHouse
@@ -26,6 +26,7 @@ Now that your data is in ClickHouse, it's time to analyze it, which often involv
 - [Tableau](./data-visualization/tableau-and-clickhouse.md)
 - [Looker](./data-visualization/looker-and-clickhouse.md)
 - [Metabase](./data-visualization/metabase-and-clickhouse.md)
+- [Mitzu](./data-visualization/mitzu-and-clickhouse.md)
 - [Superset](./data-visualization/superset-and-clickhouse.md)
 - [Deepnote](./data-visualization/deepnote.md)
 - [Draxlr](./data-visualization/draxlr-and-clickhouse.md)
@@ -45,7 +46,8 @@ Now that your data is in ClickHouse, it's time to analyze it, which often involv
 | [Looker](./data-visualization/looker-and-clickhouse.md)                 | Native connector              | ✅      | ✅          | Works with some limitations, see [the documentation](./data-visualization/looker-and-clickhouse.md) for more details         |
 | Looker                                                                  | MySQL interface               | 🚧     | ❌          |                                                                                                                              |
 | [Looker Studio](./data-visualization/looker-studio-and-clickhouse.md)   | MySQL interface               | ✅      | ✅          |                                                                                                                              |
-| [Metabase](./data-visualization/metabase-and-clickhouse.md)             | ClickHouse official connector | ✅      | ✅          |                                                                                                                              |
+| [Metabase](./data-visualization/metabase-and-clickhouse.md)             | ClickHouse official connector | ✅      | ✅          |                                                                                                        
+| [Mitzu](./data-visualization/mitzu-and-clickhouse.md)             |  Native connector | ✅      | ✅          |                                                                                                                              |
 | [Power BI Desktop](./data-visualization/powerbi-and-clickhouse.md)      | ClickHouse official connector | ✅      | ✅          | Via ODBC, not suitable for large workloads (no direct query mode)                                                            |
 | Power BI service                                                        | ClickHouse official connector | 🚧     | ❌          |                                                                                                                              |
 | [Rocket BI](./data-visualization/rocketbi-and-clickhouse.md)            | Native connector              | ✅      | ❌          |                                                                                                                              |

docs/en/integrations/data-visualization/mitzu-and-clickhouse.md

@@ -0,0 +1,165 @@
+---
+sidebar_label: Mitzu
+slug: /en/integrations/mitzu
+keywords: [clickhouse, mitzu, connect, integrate, ui]
+description: Mitzu is a no-code warehouse-native product analytics application.
+---
+
+import ConnectionDetails from '@site/docs/en/\_snippets/\_gather_your_details_http.mdx';
+
+# Connecting Mitzu to ClickHouse
+
+Mitzu is a no-code warehouse-native product analytics application. Just like Amplitude, Mixpanel or Posthog, Mitzu enables it's users to
+query the product usage data without any SQL or Python knowledge. Mitzu instead copy the company's product usage data, it generates native SQL
+queries over the company's data warehouse or lake.
+
+## Goal
+
+In this guide we are going to cover:
+
+- Warehouse-native product analytics
+- How to integrate Mitzu to Clickhouse
+
+:::tip Example datasets
+If you do not have a data set to use for Mitzu, you can work with NYC Taxi Data.
+This dataset is available in Clickhouse Cloud.
+:::
+
+## 1. Gather your connection details
+
+<ConnectionDetails />
+
+## 2. Sign in or sign up to Mitzu
+
+As a first step head to [https://app.mitzu.io](https://app.mitzu.io) for sign up.
+
+<img src={require('./images/mitzu_01.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Sign in" />
+
+## 3. Create your workspace
+
+After creating an organization, you will be prompted to create your first workspace.
+
+<img src={require('./images/mitzu_02.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Create workspace" ></img>
+
+## 4. Connect Mitzu to ClickHouse
+
+Once your workspace is created, you need to manually set the connection details.
+
+<img src={require('./images/mitzu_03.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}}alt="Setup connection details" ></img>
+
+In the guided onboarding Mitzu enables to integrate with a single table.
+
+> In order to run product analytics on your clickhouse setup, you need to > specify a few key columns from your table.
+>
+> These are the following:
+>
+> - **User id** - the column for the unique identifier for the users.
+> - **Event time** - the timestamp column of your events.
+> - Optional[**Event name**] - in case the table contains multiple event types, this column segments the events.
+
+<img src={require('./images/mitzu_04.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Setup table connection"></img>
+
+<br/>
+
+:::tip Adding more tables
+Adding more tables is possible once the initial guided setup is done.
+See below.
+:::
+
+## 5. Create an event catalog
+
+The final step of the onboarding is the `Event catalog` creation.
+
+<img src={require('./images/mitzu_05.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Create event catalog" ></img>
+
+This step finds all events and its properties from the above defined table.
+This step may take up to a few minutes, depending on the size of your dataset.
+
+If everything went well, you will ready to explore your events.
+<img src={require('./images/mitzu_06.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Explore" width="300px"></img>
+
+## 4. Run segmentation queries
+
+User segmentation in Mitzu is just as easy as in Amplitude, Mixpanel or Posthog.
+
+You can select the events on the left side of the explore page, while configuring the time horizont is on the top part.
+
+<img src={require('./images/mitzu_07.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Segmentation" ></img>
+
+<br/>
+
+:::tip Filters and Breakdown
+Filtering is done like you would expect, pick a property (clickhouse column) and select the values from the dropdown that you want to filter.
+For breakdowns you choose any event or user property (see below how to integrate user properties).
+:::
+
+## 5. Run funnel queries
+
+Select up to 9 steps for a funnel. Choose the time window for within the funnel can be finished by your users.
+Get immediate conversion rate insights, without writing a single line of SQL code.
+
+<img src={require('./images/mitzu_08.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Funnel" ></img>
+
+<br/>
+
+:::tip Visualize trends
+Pick `Funnel trends` to visualize funnels trends over time.
+:::
+
+## 6. Run retention queries
+
+Select up to 2 steps for a retention rate calculation. Choose the retention window for selecting the recurring window for
+Get immediate conversion rate insights, without writing a single line of SQL code.
+
+<img src={require('./images/mitzu_09.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Retention" ></img>
+
+<br/>
+
+:::tip Cohort retention
+Pick `Weekly cohort retention` to visualize how your retention rates are changing over time.
+:::
+
+## 7. SQL native
+
+Mitzu is SQL Native, this means it generates native SQL code from the configuration that you have chosen on the Explore page.
+
+<img src={require('./images/mitzu_10.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="SQL Native" ></img>
+
+<br/>
+
+:::tip Continue your work in a BI tool
+If you run into a limitation with Mitzu UI, simple copy the SQL code and continue your work in a BI tool.
+:::
+
+## 8. Adding more event tables
+
+If you store your product usage events in multiple tables, you can add those as well to your event catalog.
+Go to the workspace settings page (gear icon at the top of the page), select the event tables tab.
+
+Add the remaining event tables from your Clickhouse warehouse.
+
+<img src={require('./images/mitzu_11.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Extra tables" ></img>
+
+<br/>
+
+Once you added all other event tables to your workspace. You need to configure those as well.
+Configure the **user id**, **event time** and optionally the **event name** columns.
+
+<img src={require('./images/mitzu_12.png').default} class="image" style={{width: '50%', 'background-color': 'transparent'}} alt="Configure tables" ></img>
+
+Click the configure tables button and set these columns in a bulk.
+You can add up to 5000 tables to Mitzu.
+
+Last but not least don't forget to **Save and update event catalog**.
+
+## Mitzu support
+
+If you are lost feel free to contact us at [[email protected]](email://[email protected])
+
+Or you our Slack community [here](https://join.slack.com/t/mitzu-io/shared_invite/zt-1h1ykr93a-_VtVu0XshfspFjOg6sczKg)
+
+## Learn more
+
+Find more information about Mitzu by at [mitzu.io](https://mitzu.io)
+
+Visit our documentations page at [docs.mitzu.io](https://docs.mitzu.io)

docs/en/integrations/index.mdx

@@ -159,6 +159,7 @@ We are actively compiling this list of ClickHouse integrations below, so it's no
 |Mage|<img src={require('./images/logos/mage.jpg').default} class="image" alt="Metaplane logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|Data Ingestion|Open-source data pipeline tool for transforming and integrating data|[Documentation](https://docs.mage.ai/integrations/databases/ClickHouse)
 |Metaplane|<img src={require('./images/logos/logo_metaplane.png').default} class="image" alt="Metaplane logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|Data management|Data observability for every data team|[Website](https://www.metaplane.dev/integrations)|
 |MindsDB|<img src={require('./images/logos/logo_mindsdb.png').default} class="image" alt="MindsDB logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|AI/ML|MindsDB introduces ML to the data’s source – inside the database|[Website](https://mindsdb.com/clickhouse-machine-learning )|
+|Mitzu|<img src={require('./images/logos/logo_mitzu.png').default} class="image" alt="Mitzu logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|Data visualization|Mitzu is a no-code warehouse-native product analytics application. Find funnel, retention, user segmentation insights without copying your data.|[Documentation](/docs/en/integrations/mitzu)|
 |Mode Analytics|<img src={require('./images/logos/logo_mode.png').default} class="image" alt="Mode logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|Data visualization|Business Intelligence built around data teams|[Website](https://mode.com/)|
 |Openblocks|<img src={require('./images/logos/logo_openBlocks.png').default} class="image" alt="Openblocks logo" style={{width: '3rem', 'background-color': 'transparent'}}/>|SQL client|Openblocks is a low code platform for building UIs|[Documentation](https://docs.openblocks.dev/data-sources/connect-to-databases/clickhouse/)|
 |Prequel|<PrequelSVG style={{width: '3rem'}} />|Data sharing|Connect your ClickHouse instance to Prequel to share data to or sync data from your users and partners.|[Documentation](https://docs.prequel.co/docs/sources-clickhouse-generic)|

docusaurus.config.js

@@ -456,6 +456,10 @@ const config = {
 						from: '/en/connect-a-ui/metabase-and-clickhouse',
 						to: '/en/integrations/metabase',
 					},
+					{
+						from: '/en/connect-a-ui/mitzu-and-clickhouse',
+						to: '/en/integrations/mitzu',
+					},
 					{
 						from: '/en/connect-a-ui/rocketbi-and-clickhouse',
 						to: '/en/integrations/rocketbi',

sidebars.js

@@ -266,6 +266,7 @@ const sidebars = {
             'en/integrations/data-visualization/looker-and-clickhouse',
             'en/integrations/data-visualization/looker-studio-and-clickhouse',
             'en/integrations/data-visualization/metabase-and-clickhouse',
+            'en/integrations/data-visualization/mitzu-and-clickhouse',
             'en/integrations/data-visualization/powerbi-and-clickhouse',
             'en/integrations/data-visualization/quicksight-and-clickhouse',
             'en/integrations/data-visualization/rocketbi-and-clickhouse',