diff --git a/docs/integrate/framework.md b/docs/integrate/framework.md
index d23e479..fb422ae 100644
--- a/docs/integrate/framework.md
+++ b/docs/integrate/framework.md
@@ -31,6 +31,64 @@ infrastructure to framework integrations.
:::::
+(dash)=
+## Dash
+
+```{div}
+:style: "float: right"
+[{w=180px}](https://dash.plotly.com/)
+```
+
+[Dash] is a low-code framework for rapidly building data apps in Python,
+based on [Plotly]. Built on top of Plotly.js, React and Flask, Dash ties
+modern UI elements like dropdowns, sliders, and graphs, directly to your
+analytical Python code.
+
+Dash is a trusted Python framework for building ML & data science web apps. Many
+specialized open-source Dash libraries exist that are tailored for building
+domain-specific Dash components and applications.
+
+```{div}
+:style: "clear: both"
+```
+:::
+
+{h=200px}
+{h=200px}
+
+:::{dropdown} **Dash Enterprise**
+```{div}
+:style: "float: right"
+[{w=180px}](https://plotly.com/dash/)
+```
+
+Dash Enterprise is Plotly’s paid product for building, testing, deploying, managing,
+and scaling Dash applications organization-wide, advertised as the Premier Data App
+Platform for Python.
+
+When building Dash apps in a business setting, Dash Enterprise supports you to deploy
+and scale them, plus integrate them with IT infrastructure such as authentication and
+VPC services, in order to deliver faster and more impactful business outcomes on AI
+and data science initiatives.
+
+Dash Enterprise enables the rapid development of production-grade data apps within your
+business. Python has taken over the world, and traditional BI dashboards no longer
+cut it in today’s AI and ML driven world. Production-grade, low-code Python data apps
+are needed to visualize the sophisticated data analytics and data pipelines that run
+modern businesses.
+
+```{div}
+:style: "clear: both"
+```
+{h=200px}
+{h=200px}
+:::
+
+
+
+_Plotly Dash Course - Session 1._
+
+
(gradio)=
## Gradio
@@ -56,6 +114,70 @@ machine learning model demo applications, written in Python.
_How to Build Machine Learning APIs Using Gradio._
+(hvplot)=
+## hvPlot and Datashader
+
+```{div}
+:style: "float: right"
+[{w=220px}](https://hvplot.holoviz.org/)
+
+[{w=220px}](https://datashader.org/)
+```
+
+[hvPlot] is a familiar and high-level API for data exploration and visualization.
+[Datashader] is a graphics pipeline system for creating meaningful representations of
+large datasets quickly and flexibly.
+
+It is used on behalf of the [hvPlot] package, which is based on [HoloViews], from the
+family of [HoloViz] packages of the [PyViz] ecosystem.
+
+With Datashader, you can "just plot" large datasets and explore them instantly, with no
+parameter tweaking, magic numbers, subsampling, or approximation, up to the resolution
+of the display.
+
+[hvPlot] sources its power in the [HoloViz] ecosystem. With [HoloViews], you get the
+ability to easily layout and overlay plots, with [Panel], you can get more interactive
+control of your plots with widgets, with [DataShader], you can visualize and interactively
+explore very large data, and with [GeoViews], you can create geographic plots.
+
+```{div}
+:style: "clear: both"
+```
+
+{h=200px}
+{h=200px}
+
+
+
+
+_hvPlot and Panel: Visualize all your data easily, from notebooks to dashboards | SciPy 2023._
+
+
+(plotly)=
+## Plotly
+
+```{div}
+:style: "float: right"
+[{w=180px}](https://plotly.com/)
+```
+
+[Plotly] Open Source Graphing Libraries make interactive, publication-quality graphs.
+Line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms,
+heatmaps, subplots, multiple-axes, polar charts, bubble charts, and maps.
+
+The supported programming languages / libraries / frameworks are Python, R, Julia,
+JavaScript, ggplot2, F#, MATLAB®, and Dash.
+
+Based on Plotly, [Dash] is a low-code framework for rapidly building data apps in Python.
+
+```{div}
+:style: "clear: both"
+```
+
+{h=200px}
+{h=200px}
+
+
(streamlit)=
## Streamlit
@@ -84,6 +206,14 @@ out Python data applications. It provides fast, interactive prototyping, and liv
_Streamlit 101 - A faster way to build and share data applications._
+[Dash]: https://plotly.com/dash/
+[Datashader]: https://datashader.org/
[Gradio]: https://www.gradio.app/
+[HoloViews]: https://www.holoviews.org/
+[HoloViz]: https://holoviz.org/
+[hvPlot]: https://hvplot.holoviz.org/
[Hugging Face]: https://en.wikipedia.org/wiki/Hugging_Face
+[Panel]: https://panel.holoviz.org/
+[Plotly]: https://plotly.com/graphing-libraries/
+[PyViz]: https://pyviz.org/
[Streamlit]: https://streamlit.io/
diff --git a/docs/integrate/visualize.md b/docs/integrate/visualize.md
index 829a021..bb303ec 100644
--- a/docs/integrate/visualize.md
+++ b/docs/integrate/visualize.md
@@ -2,7 +2,8 @@
# Visualize data in CrateDB
Dashboard and other data visualization applications and toolkits for
-visualizing data stored inside CrateDB.
+visualizing data stored inside CrateDB, mostly dashboarding.
+
::::{card} {material-outlined}`lightbulb;2em` Tutorials
:margin: 0 0 5 5
@@ -86,59 +87,6 @@ your entire company in few minutes.
{h=200px}
-## Dash
-
-```{div}
-:style: "float: right"
-[{w=180px}](https://dash.plotly.com/)
-```
-
-[Dash] is a low-code framework for rapidly building data apps in Python,
-based on [Plotly]. Built on top of Plotly.js, React and Flask, Dash ties
-modern UI elements like dropdowns, sliders, and graphs, directly to your
-analytical Python code.
-
-Dash is a trusted Python framework for building ML & data science web apps. Many
-specialized open-source Dash libraries exist that are tailored for building
-domain-specific Dash components and applications.
-
-```{div}
-:style: "clear: both"
-```
-:::
-
-{h=200px}
-{h=200px}
-
-:::{dropdown} **Dash Enterprise**
-```{div}
-:style: "float: right"
-[{w=180px}](https://plotly.com/dash/)
-```
-
-Dash Enterprise is Plotly’s paid product for building, testing, deploying, managing,
-and scaling Dash applications organization-wide, advertised as the Premier Data App
-Platform for Python.
-
-When building Dash apps in a business setting, Dash Enterprise supports you to deploy
-and scale them, plus integrate them with IT infrastructure such as authentication and
-VPC services, in order to deliver faster and more impactful business outcomes on AI
-and data science initiatives.
-
-Dash Enterprise enables the rapid development of production-grade data apps within your
-business. Python has taken over the world, and traditional BI dashboards no longer
-cut it in today’s AI and ML driven world. Production-grade, low-code Python data apps
-are needed to visualize the sophisticated data analytics and data pipelines that run
-modern businesses.
-
-```{div}
-:style: "clear: both"
-```
-{h=200px}
-{h=200px}
-:::
-
-
## Explo
```{div}
@@ -208,39 +156,6 @@ Get Grafana fully managed with [Grafana Cloud].
:::
-## hvPlot and Datashader
-
-```{div}
-:style: "float: right"
-[{w=220px}](https://hvplot.holoviz.org/)
-
-[{w=220px}](https://datashader.org/)
-```
-
-[hvPlot] is a familiar and high-level API for data exploration and visualization.
-[Datashader] is a graphics pipeline system for creating meaningful representations of
-large datasets quickly and flexibly.
-
-It is used on behalf of the [hvPlot] package, which is based on [HoloViews], from the
-family of [HoloViz] packages of the [PyViz] ecosystem.
-
-With Datashader, you can "just plot" large datasets and explore them instantly, with no
-parameter tweaking, magic numbers, subsampling, or approximation, up to the resolution
-of the display.
-
-[hvPlot] sources its power in the [HoloViz] ecosystem. With [HoloViews], you get the
-ability to easily layout and overlay plots, with [Panel], you can get more interactive
-control of your plots with widgets, with [DataShader], you can visualize and interactively
-explore very large data, and with [GeoViews], you can create geographic plots.
-
-```{div}
-:style: "clear: both"
-```
-
-{h=200px}
-{h=200px}
-
-
## Metabase
```{div}
@@ -285,51 +200,18 @@ with none of the work or hidden costs that come with self-hosting.
:::
-## Plotly
-
-```{div}
-:style: "float: right"
-[{w=180px}](https://plotly.com/)
-```
-
-[Plotly] Open Source Graphing Libraries make interactive, publication-quality graphs.
-Line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms,
-heatmaps, subplots, multiple-axes, polar charts, bubble charts, and maps.
-
-The supported programming languages / libraries / frameworks are Python, R, Julia,
-JavaScript, ggplot2, F#, MATLAB®, and Dash.
-
-Based on Plotly, [Dash] is a low-code framework for rapidly building data apps in Python.
-
-```{div}
-:style: "clear: both"
-```
-
-{h=200px}
-{h=200px}
-
-
-
[Apache Superset]: https://superset.apache.org/
[Cluvio]: https://www.cluvio.com/
[CrateDB and Grafana]: https://cratedb.com/integrations/cratedb-and-grafana
[CrateDB and Superset]: https://cratedb.com/integrations/cratedb-and-apache-superset
[CrateDB and Metabase]: https://cratedb.com/integrations/cratedb-and-metabase
-[Dash]: https://plotly.com/dash/
-[Datashader]: https://datashader.org/
[Explo]: https://www.explo.co/
[Explo Explore]: https://www.explo.co/products/explore
[GeoViews]: https://geoviews.org/
[Grafana Cloud]: https://grafana.com/grafana/
[Grafana Labs]: https://grafana.com/about/team/
[Grafana OSS]: https://grafana.com/oss/grafana/
-[HoloViews]: https://www.holoviews.org/
-[HoloViz]: https://holoviz.org/
-[hvPlot]: https://hvplot.holoviz.org/
[Metabase]: https://www.metabase.com/
[Metabase Cloud]: https://www.metabase.com/cloud/
-[Panel]: https://panel.holoviz.org/
-[Plotly]: https://plotly.com/graphing-libraries/
[Preset]: https://preset.io/
[Preset Cloud]: https://preset.io/product/
-[PyViz]: https://pyviz.org/