SAP Analytics Cloud

Adding new fields to the existing analytic data model (imported or acquired data connection) – SAP Analytics Cloud

Introduction

In this blog post, we will explore the steps to deal with the above scenario. Here is my case, the data is fetched from the S/4HANA Cloud system and the data connection in SAP Analytics Cloud (SAC) is through OData Services. This blog post will be helpful for BW/BI consultants who are new to SAC and its features and for those who would want to attempt for certification.

Main Part (Step By Step Flow)

  • Make sure that the field to be added in the SAC model is available in the source system. In my scenario, I have made sure that the new field is available in the OData endpoint which I have given in the SAC connection.
  • In the SAC model’s workspace, click on the Model Structure.
  • Create a skeleton of the new field to be added in SAC and In-order to do that…

a) Click on the Edit (+) icon and then click on “Add new Dimension”.

b) Enter the new field name in the create dimension dialog box (preferably as it is in the source system) and click on the Add button.

  • After successful creation, click on the save icon (in the General section) to save the changes and click on the “Data management” option from the model’s workspace.
  • Select “Datasource” by clicking on the ‘import data’ icon and select Odata Services from the data source wizard.
  • Select your data connection from the drop-down, click on the “create a new query” radio button and finally click on the add button.
  • Enter the query name and click “Freehand Query” in the query wizard. Inside the query, textbox enter your old data query and include the new field name to be added as shown below.
  • Click on next and you will be able to see your newly created draft source.
  • Double click on the draft data source in order to open the mapping wizard.
  • Click on the “combine data” icon from the actions tab if you wanted to add more data queries else skip this step.
  • Make sure that there are no mapping issues and it can be found in the “Model Requirement” section.

The field names same as the ones in the existing model are mapped automatically. If there are unmapped dimensions or if the field names are different from the existing model you should map them manually. Here I have two issues and I have resolved them below.

a) Unmapped dimension – Field “TestNewField” is unmapped, filter the left pane by clicking on the ‘Unmapped first’ option. Drag and drop the respective fields from left to right.

b) Data quality issue – I have a date field that exceeds the limit range and I have fixed it using the smart transformation functions.

  • Once all the issues are fixed, click on the ‘clean and replace selected version data’ under the import method section. This is like a clean wipe-out of existing data for the selected version and replacement with new data.
  • Click on ‘finish mapping’, your mapping will be validated and your data will be imported from your source. Your newly added data source will be now available under the import jobs section.
  • Hurray! You will be now able to see the newly added field in your story.

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