1. DB platform: SAP HANA: The HDMS leverages HANA platform which means all of its components runs on HANA with all benefits of the HANA like in memory computing, advance DB capabilities, different engines (spatial/graph processing, text analysis, search and mining, predictive/machine learning, streaming, series data storage and processing), etc.
2. Orchestration and governance: SAP Data Hub is used to centralize metadata management cross different systems. Main function of this component are:
- Data Pipelines – flow based applications consisting of reusable and configurable operations, e.g. ETL, Preparation, Code Execution, Connectors
- Workflows – orchestrate processes across the data landscape, e.g. executing data pipelines, triggering SAP BW Process Chains, SAP Data Services Jobs and many more.
- Governance – metadata repository of information stored in the connected landscape. Offering discovery, profiling and search capabilities.
3. Multi-modal modeling: SAP Enterprise Architecture Designer (EA Designer or EAD) is used as component of the HDMS to model systems in landscape and processes around it. Is it to use for conceptual, logical, and physical modeling of SAP and non-SAP data.
4. Cloud services: SAP Cloud Platform Big Data Services component is used to deliver full-service big data cloud based on Hadoop and Spark.
Tools of SAP HDMS:
SAP HANE Extended Application Services (XSA/Cloud Foundry)
SAP HANA Web IDE
SAP HANA Application Lifecycle Management (ALM)
SAP HANA Deployment Infrastructure (HDI)
SAP HANA EIM Services (SDI/SDQ); SDI = Smart Data Integration; SDQ = Smart Data Quality
SAP Enterprise Architecture Designer
SAP HANA Processing Engines & Services
SAP HANA Data Tiering
SAP HANA Data Warehousing Foundation (DWF)
SAP Agile Data Preparation (ADP)
SAP HANA Based Services on SCP
Open Source Tools like Git, Jenkins, etc.
The HDMS is part of SAP’s initiative called Intelligent Data and it shall support its customers in transition to an Intelligent Enterprise. The term Intelligent Data can be described as data (data ingestion from various sources, smart data streaming for event capture, high data quality) in a single and unified view. Together with smart data integration that enabling innovative/ advanced applications and data management.
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