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Product and Topic Expert
Product and Topic Expert
In this blog post I will share how to create an SAP Analytics Cloud (SAC), Geo Map based on Calculation Views created within the WebIDE. These are Calc Views that reside within an HDI Container as Column Views.


  1. HANA Cloud / HANA On-Prem with XSA

  2. Live Connection from SAC to HANA

  3. Dataset with Latitude and Longitude

  4. HDI Calculation Views (created via Business Application Studio or WebIDE)

Required Steps

  1. Create SAP_BOC_SPATIAL namespace

  2. Spatial Reference 3857

  3. Location Data

  4. Create Geo Dimensional Calculation View with ST_POINT

  5. Associate Calc Views in SAP Analytics Cloud Model

For the official documentation please see the SAP Analytics Cloud Help

1. Create SAP_BOC_SPATIAL namespace

For the SAC Location Dimension to be identified, your calculation view needs the correct namespace. The namespace needs to be SAP_BOC_SPATIAL

There are two ways to different ways to achieve this.

Choose either the subfolder setting or the global setting.

1a. Specify the namespace at a specific sub-folder level

This can be done by creating a .hdinamespace file in a subfolder and that sub-folder will use that setting.


Figure 1a: Subfolder Project Setting db/src/calc_views/Spatial

"name": "SAP_BOC_SPATIAL",
"subfolder": "ignore"


1b. Use the global project setting to append the hdinamespace setting as below

Figure 1b: Global Project Setting db/src/.hdinamespace

"subfolder": "append"

Warning, if you change an existing project using "ignore" then some re-work will be required.

With the Global namespace setting you the require a SAP_BOC_SPATIAL folder

SAP Analytics Cloud looks for location data inside the namspsace SAP_BOC_SPATIAL.
This should be created inside the WebIDE project src folder.

Figure 2: SAP_BOC_SPATIAL folder


3. Spatial Reference 3857

For SAC to visualise the location data, HANA must have the Spatial Reference 3857 available.
We can check this with the public synonym ST_SPATIAL_REFERENCE_SYSTEMS.



If you do NOT see the SRS_ID 3857 then you can execute the SQL below to add that
COORDINATE X BETWEEN -20037508.3427892447 AND 20037508.3427892447 COORDINATE Y BETWEEN -19929191.7668547928 AND 19929191.766854766 ORGANIZATION "EPSG" IDENTIFIED BY 3857
DEFINITION 'PROJCS["Popular Visualisation CRS / Mercator",GEOGCS["Popular Visualisation CRS",DATUM["Popular_Visualisation_Datum",SPHEROID["Popular Visualisation Sphere",6378137,0,AUTHORITY["EPSG","7059"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY[ "EPSG","6055"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree", 0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4055"]],UNIT[ "metre",1,AUTHORITY["EPSG","9001"]],PROJECTION["Mercator_1SP"],PARAMETER["cen tral_meridian",0],PARAMETER["scale_factor",1],PARAMETER["false_easting",0],PA RAMETER["false_northing",0],AUTHORITY["EPSG","3785"],AXIS["X",EAST],AXIS["Y", NORTH]]'
TRANSFORM DEFINITION '+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0 +y_0=0 +k=1.0 +units=m +nadgrids=@null
+wktext +no_defs'


4. Location Data

The location dataset must not contain duplicate values.  To perform the correct join SAC requires a unique list of locations to ensure referential integrity of your model. This dataset will need latitude, longitude data and a field that joins to other Calc Views.

Here I have the table of UK Local Authorities, LAD2019_WKT, sorted on the field lad19cd, which I can see is unique.

Figure 4: Location Dataset


5. Create Geo Dimensional Calculation View with ST_POINT

We can now create a new dimensional Calculation View inside the SAP_BOC_SPATIAL folder. Notice how the Namespace field is populated with the required folder name.

Figure 5: New Dimensional Calc View, notice the Namespace: SAP_BOC_SPATIAL


The output column names need to be unique across the two calculation views that you are using with SAC. I therefore appended _geo to the end of the lad19cd and lad19nm.

Figure 6: Location Dimensional Calculation View


Create Calculated Column of data type ST_POINT.

Using the fields "long" and "lat" we generate the ST_POINT column that SAP Analytics Cloud requires using the SRS 3857.
ST_Transform(ST_GeomFromText('POINT(' || "long" || ' ' || "lat" || ')', 4326),3857)

Figure 7: Calculated Column, LOCAL_AUTHORITY_GEO ST_POINT

By specifying the "Key" column, SAC can identify which is the description field as it won't be the key.

Figure 7.1: Specify the Key Field

We can Save and Build the Calculation View.

Figure 8: Build Calculation View

We can find our Calculation View as a Column View. Note how the name is prefixed with SAP_BOC_SPATIAL (the subfolder we created in step 2.)

Figure 9: Database Explorer Column View

We should data preview it to verify it works as expected. Note how the name is again prefixed with SAP_BOC_SPATIAL.

Figure 10: Data Preview of Local Authority Calc View


6. Associate Calc Views in SAP Analytics Cloud Model

Open an existing SAC Model that will join to the fields exposed in the above model, in my case I can join on either lad19cd_geo or lad19nm_geo. Click the "Location Dimension" button.

Figure 11: Open Existing SAC HANA Model

We need to associate our Geo Dimensional Calc View with an existing calculation view.

The Location Identifier comes from an existing calculation view, this is the Attribute Column that joins to the Identifier for Mapping column coming from the step 5 "Geo Dimensional Calculation View".  In my case Area_code joins to lad19cd_geo. This would be a 1:1 or many:1 with the many coming from the existing calculation view.

Figure 12: Create Location Dimension

The final test is to create a Geo Map using this model to verify both the data and locations are   displayed correctly on the map.

Figure 13: SAP Analytics Cloud Geo Map


Spatial data has become more prevalent within the Enterprise, using SAP Analytics Cloud with HANA is a convenient way to visual this.  From this blog post you can understand how SAP Business Application Studio or WebIDE based Calculation Views from HANA or HANA Cloud can be consumed live.