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SAP Analytics Cloud content: A guide to Geo Features


In this blogpost you will learn how you can customize geo models that are delivered with SAP Analytics Cloud content, even if your data source does not provide latitude and longitude information.


Prerequisites

In this blogpost, we assume that you have already installed the content successfully. If that is not the case, please read this post or the documentation first.


For our example, we will use the SAP_PPM_PROJECTPORTFOLIO story which is based on the model SAP__PPM_IM_PORTFOLIOGEO. On the context page, you can see a geo map with a bubble layer. The size and color of the bubbles indicate the expected commercial value of the project at this location. The table on the right hand side shows additional information such as the Assessed Risk.

In order to update the model with new geo dimensions and add geo information even if the data source does not provide latitude and longitude values, there will be 2 steps:

Please be aware of the consequences of modified content. Please refer to chapter 3.2 of the SAP Analytics Cloud content documentation to avoid accidental overwriting and data loss.

 

 1. Update the Geo Locations using a flat file

1.1 As we know that we do not want to re-use any of the demo location dimensions, clear the model demo data from the model SAP__PM_IM_PORTFOLIOGEO so that we can edit the master data.

For the private dimensions (those that do not have a globe attached) we can now be sure that there is no more transactional data which is using the Dimension Location and enter the model and delete all rows in the Dimension Location and Save the model.

1.2 Next, you should prepare a flat file which contains all of the needed Project Locations and Project Names along with latitude and longitude values and one dummy measure that can be mapped. This data has to correspond to the data that you will load in Step 2.

If you are unsure which source query to use check the SAP Analytics Cloud content PDF Documentation. You can find the information in the model SAP__PPM_IM_PORTFOLIO.

For my example I will have 2 projects in 2 different locations:

Project Name;Location;latitude;longitude;Assessed Risk
Project1;Project1;49.2937323;8.6394704;1
Project2;Project2;49.2766293;-123.1181467;1

1.3 Since Project Name is a Public Dimension, we add our master data to the dimension. I have added Project 1 and Project 2 to the Project Name Dimension.

Now, we can import our new geo coordinates.

1.4 First of all, import the data from an excel or csv file as outlined above into the model.

1.5 During modelling, makes sure you unselect the option to fill applicable empty ID cells with a default value.

1.6 In my example, most of the dimensions and measure were mapped automatically. If that is not the case, go ahead and map them manually. For those dimensions, that do not exist in the source file, select any default value.

1.7 Click on the Location Dimension and select the ST Point Project_Location. On the right hand side click “Map Locations”. Now, map the tooltip as well as latitude and longitude information. Finish the mapping.

1.8 After finishing the mapping, the model will open and you can check the Location dimensions to see if everything was created correctly. If you like, you could also update the descriptions.

1.9 In addition to adequately setting geolocations for the projects, the previous flat file upload generated dummy transactional data (including the dummy “Assessed Risk” measure). Clear the model before continuing.

2. Import transactional data from the SAP BW Query

Now that our location dimension is updated, we can go ahead and import transactional data from the BW Query. The SAP Analytics Cloud content PDF Documentation gives the name of the BW Query used for the model SAP__PPM_IM_PORTFOLIO: Base-Line Reporting of Item Versions (0RPM_DS06_Q0008).

In my case, the BW Query returns the following data:

Planned Finish Date;Project;Project Type;Geo Area;Location;Assessed Risk;Probability Technical Success;Probability Commercial Success;Expected Commercial Value (manual);Net Present Value
01.05.18;Project1;PT3;PGA1;Project1;0,7;0,75;0,75;3343950000;-50503500
01.02.19;Project2;PT3;PGA2;Project2;0,65;0,55;0,6;2245550000;172000

2.1 Import the data into your model and map the dimensions and measures.

For the Location Dimension you only need to map the ID:

2.2 Open the story SAP__PPM_PROJECTPORTFOLIO and go to page Context2. You will see, that initially the page is empty. This is due to the page filter on project. Delete the page filter:

Now you will see, that the map and the Project table are updated.

Here is an overview of the Geo enriched models in SAP Analytics Cloud content and the stories that are based on those:

Model

Story Name

Page Name

SAP__FI_CA_IM_OVERDUEBPGEO

SAP__FI_CA_ANALYSIS
SAP__UTL_RA_ANALYSIS

Context

SAP__EHS_EM_IM_EMISSIONSGEO2

SAP__EHS_EM_EMISSIONS
SAP__MIL_EHS_EM_EMISSIONS SAP__OAG_EHS_EM_EMISSIONS

Content

SAP__EHS_HS_IM_INCIDENTSGEO

SAP__EHS_HS_INCIDENTS
SAP__MIL_EHS_HS_INCIDENTS SAP__OAG_EHS_HS_INCIDENTS

Incident_Context

SAP__PPM_IM_PORTFOLIOGEO

SAP__PPM_PROJECTPORTFOLIO
SAP__OAG_PPM_PROJECTPORTFOLIO
SAP__UTL_PPM_PROJECTPORTFOLIO

Context2

SAP__UTL_GEN_IM_SALESGEO

SAP__UTL_RM_RENEWABLE

Context

SAP__HR_GEN_IM_EC_HEADCOUNT

SAP__HR_GEN_HEADCOUNT

Overview

Leave us a comment below in case you have any questions or suggestions how content could be improved.

Related Resources

SAP Analytics Cloud content PDF Documentation

Overview of existing packages on the SAP Analytics Cloud Website or in the Roll-out Slide Deck

You want to see more blogs about SAP Analytics Cloud content? Go to our main blog or check out the tag SAP Analytics Cloud content on SCN.

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