Technology Blogs by SAP
Learn how to extend and personalize SAP applications. Follow the SAP technology blog for insights into SAP BTP, ABAP, SAP Analytics Cloud, SAP HANA, and more.
cancel
Showing results for 
Search instead for 
Did you mean: 

Introduction:


When working in ETL and data engineering in SAP Data Warehouse Data Builder there are several reasons you should want to remove empty strings, for example when constructing dimensions views usually should avoid items without description since they could duplicate dimension members, take as an example next case:





















SKU ID Description Material Color
112233 Connector Tin blue
112234 Tin blue

this scenario is very common in master data coming from other non SAP systems, it could affect seriously your measures and data models, and that's why we will see how to easily remove them.

Prerequisites:



  1. You have a SAP Data Warehouse Cloud Tenant

  2. You have your own Space

  3. You have a table with some fields containing empty strings


Implementing the Filter artifact with the TRIM function:


1. Get into SAP Data Warehouse Data Builder and open/create a view containing your table with some fields containing empty strings.

2. Select your table and active "Distinct Values: ON" from the displayed menu

3. Add a Filter artifact


Filter artifact


 

4. Click or select the Filter artifact and select the corresponding column to enable it in the Expression editor:


Column selection


 

5. Inside the expression editor exclude all null values using: yourcolumnname IS NOT NULL syntax condition, eventually after removing all spaces from your strings you will effectively remove empty strings using a simple condition: LTRIM(RTRIM(yourcolumnname ) ) != ' '

6. Validate your expression using the button Validate and check the expected outcome

 


Excluding nulls and empties


 

Conclusion:


Since SAP Data Warehouse Cloud allows ingesting data practically from every type of source(Systems, DBMS, Files, etc)  using this simple method you can exclude null values and empty strings to bring reliability to your data models.

Thank you for reading