In this blogpost I will describe how you can use the SAP Analytics Cloud choropleth layers to visualise HANA spatial clusters, such as grid, k-means or hexagons.
With that in place the steps are pretty easy
1. Create database view (or table) to encapsulate spatial clustering
2. Expose database view as Dimension Calculation View
3. Update SAC Custom Regions Metadata
4. Visualise with SAP Analytics Cloud
5. Other Possibilities, Voronoi Regions
1. Create database view (or table) to encapsulate spatial clustering
The spatial clustering require spatial data with an ST_POINT datatype, this can be calculated from longitude and latitude if necessary.
Figure 1.1: Database Explorer data preview
Figure 1.2: Database view with Hexagon Clustering
VIEW "view::LAD_2019_HEX15" AS
SELECT COUNT(*) AS LAD_COUNT, ST_ClusterID() AS ID, ST_ClusterCell() AS SHAPE_HEX
FROM LAD2019_ST
GROUP CLUSTER BY ST_POINT USING HEXAGON X CELLS 15
2. Expose database view as Dimension Calculation View
SAP Analytics Cloud requires a dimensional calculation view with 4 fields exposed
◉ NAME
◉ ID
◉ SHAPE
◉ IS_LEAF
The output of the Calculation view should contain these fields. ID and IS_LEAF are required as column names
Figure 2.1 Calculation View
Figure 2.2: Data Preview
3. Update SAC Custom Regions Metadata
You need to update the metadata to tell SAC that a new choropleth layer is available.
INSERT INTO "SAP_FPA_SPATIAL_CUSTOM_REGIONS"."sap.fpa.services.spatial::custom_hierarchy.CHOROPLETH_CUSTOM_HIERARCHY" VALUES (
'Hexagons', 5, 'CLUSTER_NAME', 'name', 13, 1, 'Hexagons 15', 'SHAPE_HEX', 'cv::ENGLAND_HEX_15', '', 'COVID', '0');
SELECT * FROM "SAP_FPA_SPATIAL_CUSTOM_REGIONS"."sap.fpa.services.spatial::custom_hierarchy.CHOROPLETH_CUSTOM_HIERARCHY";
You can check the metadata looks as expected
Figure 3.1: Preview SAC Custom Spatial Regions
4. Visualise with SAP Analytics Cloud
Within SAC you can create a Geo Map with a Choropleth / Drill Layer and you should see the newly exposed view as a hierarchy.
Figure 4.1: Create Choropleth / Drill Layer
Figure 4.2: Hexagon Spatial Clustering in SAP Analytics Cloud
5. Other Possibilities, Voronoi Regions
Using exactly the same techniques you can access other spatial techniques such as Voronoi regions, as suggested by a colleague James Giffin Voronoi regions/cells sound more like a beer or wine to me, makes for an interesting visual.
VIEW "view::LAD_VORONOI" AS
SELECT "objectid" AS ID, "lad19nm" AS NAME, ST_VoronoiCell(ST_POINT, -1.0) OVER () AS VORONOI_SHAPE FROM "LAD2019_ST"
Figure 5: Voronoi Cells / Regions
Source: sap.com
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