Update documentation on new way of visualising layers on Kedro-viz (#…

…2771)

This document informs user of the new way of defining layers that was introduced in Kedro 18.9

docs/source/resources/glossary.md

@@ -38,7 +38,7 @@ You can use Kedro-Viz to visualise your Kedro data pipelines:
 ## Layers (data engineering convention)
 According to [common data engineering convention](https://towardsdatascience.com/the-importance-of-layered-thinking-in-data-engineering-a09f685edc71), a pipeline can be broken up into different layers according to how data is processed. This convention makes it easier to collaborate with other team members because everyone has an idea of what type of data cleaning or processing has happened.
 
-Kedro-Viz makes it easy to [visualise these data processing stages](../visualisation/kedro-viz_visualisation.md#visualise-layers) by adding a `layer` attribute to the datasets in the Data Catalog.
+Kedro-Viz makes it easy to [visualise these data processing stages](../visualisation/kedro-viz_visualisation.md#visualise-layers) by adding a `layer` attribute to the `kedro-viz` section within the `metadata` of the datasets in the Data Catalog.
 
 ## Modular pipeline
 _(See also [Pipeline](#pipeline))_

docs/source/visualisation/kedro-viz_visualisation.md

@@ -66,46 +66,83 @@ By convention, a [pipeline can be defined as having different layers](../resourc
 
 For example, the [data engineering convention](https://towardsdatascience.com/the-importance-of-layered-thinking-in-data-engineering-a09f685edc71) labels datasets according to the stage of the pipeline (e.g. whether the data has been cleaned).
 
-You can add a `layer` attribute to the datasets in the Data Catalog, which is reflected in the Kedro-Viz visualisation.
+In Kedro version 0.18.9 we changed the way layers are defined in the Data Catalog. The definition is now included under the `metadata` key for `kedro-viz` (previously it was an attribute specified within a dataset's definition).
 
-Open `catalog.yml` for the completed spaceflights tutorial and replace the existing code with the following:
+Here's an example of how to use the Kedro-Viz metadata to define layers:
 
 ```yaml
 companies:
   type: pandas.CSVDataSet
   filepath: data/01_raw/companies.csv
-  layer: raw
+  metadata:
+    kedro-viz:
+      layer: raw
+```
+
+In earlier versions of Kedro, layers were specified within a dataset's definition in the Data Catalog, but this will **no longer be supported** from Kedro version 0.19.0. From that version onwards, your `catalog.yml` must specify layers as metadata.
+
+```diff
+companies:
+  type: pandas.CSVDataSet
+  filepath: data/01_raw/companies.csv
+-  layer: raw
++   metadata:
++     kedro-viz:
++       layer: raw
+```
+
+Open `catalog.yml` for the completed spaceflights tutorial and define layers in the following way:
+
+```yaml
+companies:
+  type: pandas.CSVDataSet
+  filepath: data/01_raw/companies.csv
+  metadata:
+    kedro-viz:
+      layer: raw
 
 reviews:
   type: pandas.CSVDataSet
   filepath: data/01_raw/reviews.csv
-  layer: raw
+  metadata:
+    kedro-viz:
+      layer: raw
 
 shuttles:
   type: pandas.ExcelDataSet
   filepath: data/01_raw/shuttles.xlsx
-  layer: raw
+  metadata:
+    kedro-viz:
+      layer: raw
 
 preprocessed_companies:
   type: pandas.ParquetDataSet
   filepath: data/02_intermediate/preprocessed_companies.pq
-  layer: intermediate
+  metadata:
+    kedro-viz:
+      layer: intermediate
 
 preprocessed_shuttles:
   type: pandas.ParquetDataSet
   filepath: data/02_intermediate/preprocessed_shuttles.pq
-  layer: intermediate
+  metadata:
+    kedro-viz:
+      layer: intermediate
 
 model_input_table:
   type: pandas.ParquetDataSet
   filepath: data/03_primary/model_input_table.pq
-  layer: primary
+  metadata:
+    kedro-viz:
+      layer: primary
 
 regressor:
   type: pickle.PickleDataSet
   filepath: data/06_models/regressor.pickle
   versioned: true
-  layer: models
+  metadata:
+    kedro-viz:
+      layer: models
 ```
 
 The visualisation now includes the layers: