1. SAP Glossary
  2. SAP Master Data Services
  3. data architect


What is data architect in SAP EIM-MDS - SAP Master Data Services?


SAP Term: data architect

  • Component: EIM-MDS

  • Component Name: SAP Master Data Services

  • Description: A user responsible for mapping data models of various source systems to the MDS data model. Also responsible for customizing, executing, and maintaining operations that extract, transform, standardize, match, and load data from the source systems to the SAP HANA database.


Smart SAP Assistant

  • Key Concepts: 
    A data architect is a professional who designs and implements data management systems. They are responsible for creating and maintaining the structure of an organization’s data, ensuring that it is organized, secure, and accessible. In the context of SAP Master Data Services (EIM-MDS), a data architect is responsible for designing and implementing the data models that will be used to store and manage master data. 
    
    How to use it: 
    Data architects are responsible for designing and implementing the data models that will be used to store and manage master data in SAP Master Data Services (EIM-MDS). This includes creating the structure of the database, defining the relationships between different entities, and ensuring that the data is secure and accessible. The data architect must also ensure that the data models are optimized for performance and scalability. 
    
    Tips & Tricks: 
    When designing a data model for SAP Master Data Services (EIM-MDS), it is important to consider how the data will be used in the future. This includes anticipating changes in business requirements, as well as any potential scalability issues. It is also important to ensure that the data model is optimized for performance, as this can have a significant impact on system performance. 
    
    Related Information: 
    For more information on SAP Master Data Services (EIM-MDS) and how to design effective data models, please refer to the official SAP documentation. Additionally, there are many online resources available that provide tips and best practices for designing effective data models.
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