DOCS-#7287: Update Modin on Dask documentation (#7288)

Co-authored-by: Igoshev, Iaroslav <iaroslav.igoshev@intel.com>
Signed-off-by: Kirill Suvorov <kirill.suvorov@intel.com>

docs/development/using_pandas_on_dask.rst

@@ -20,4 +20,64 @@ or turn them on in source code:
 
    import modin.config as cfg
    cfg.Engine.put('dask')
-   cfg.StorageFormat.put('pandas')
+   cfg.StorageFormat.put('pandas')
+
+Using Modin on Dask locally
+---------------------------
+
+If you want to run Modin on Dask locally using a single node, just set Modin engine to ``Dask`` and 
+continue working with a Modin DataFrame as if it was a pandas DataFrame.
+You can either initialize a Dask client on your own and Modin connects to the existing Dask cluster or
+allow Modin itself to initialize a Dask client.
+
+.. code-block:: python
+
+  import modin.pandas as pd
+  import modin.config as modin_cfg
+
+  modin_cfg.Engine.put("dask")
+  df = pd.DataFrame(...)
+
+Using Modin on Dask in a Cluster
+--------------------------------
+
+If you want to run Modin on Dask in a cluster, you should set up a Dask cluster and initialize a Dask client.
+Once the Dask client is initialized, Modin will be able to connect to it and use the Dask cluster.
+
+.. code-block:: python
+
+  from distributed import Client
+  import modin.pandas as pd
+  import modin.config as modin_cfg
+  
+  # Define your cluster here
+  cluster = ...
+  client = Client(cluster)
+
+  modin_cfg.Engine.put("dask")
+  df = pd.DataFrame(...)
+
+To get more information on how to deploy and run a Dask cluster, visit the `Deploy Dask Clusters`_ page.
+
+Conversion between Modin DataFrame and Dask DataFrame
+-----------------------------------------------------
+
+Modin DataFrame can be converted to/from Dask DataFrame with no-copy partition conversion.
+This allows you to take advantage of both Modin and Dask libraries for maximum performance.
+
+.. code-block:: python
+
+  import modin.pandas as pd
+  import modin.config as modin_cfg
+  from modin.pandas.io import to_dask, from_dask
+
+  modin_cfg.Engine.put("dask")
+  df = pd.DataFrame(...)
+
+  # Convert Modin to Dask DataFrame
+  dask_df = to_dask(df)
+  
+  # Convert Dask to Modin DataFrame
+  modin_df = from_dask(dask_df)
+
+.. _Deploy Dask Clusters: https://docs.dask.org/en/stable/deploying.html