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Curriculum Designed by Experts
The SAP Datasphere Modeling Corporate Training by Multisoft Virtual Academy is designed to provide corporate teams with advanced skills in data modeling and management. Participants will learn to build, maintain, and optimize SAP Datasphere models to facilitate seamless data integration and analysis. This course combines theoretical concepts with practical exercises, enabling professionals to make informed business decisions. Suitable for data analysts, IT teams, and business users, the program enhances team productivity and organizational data expertise.
SAP Datasphere Modeling Training is a professional program that teaches how to design, manage, and optimize semantic data models using SAP Datasphere. The training focuses on integrating data from multiple SAP and non-SAP sources while preserving business context and governance. Learners gain hands-on experience with spaces, graphical and SQL views, analytical models, data flows, security, and performance optimization to deliver trusted, scalable analytics for modern cloud-based enterprises.
- Overview of SAP Datasphere and its role in modern analytics
- Evolution from SAP Data Warehouse Cloud to SAP Datasphere
- Key concepts: Business Data Fabric, semantics, and governance
- SAP Datasphere architecture and components
- Use cases and business benefits
- SAP Datasphere tenant overview
- User interface and key tools
- Working with spaces and tenants
- Connections and system landscape
- Monitoring and administration basics
- Understanding spaces and their purpose
- Creating and managing spaces
- Space-level data isolation and governance
- Assigning users, roles, and privileges
- Best practices for space design
- Connecting SAP and non-SAP data sources
- Import vs live data connections
- Data replication and remote tables
- Data access and source system management
- Introduction to data provisioning strategies
- Modeling concepts in SAP Datasphere
- Fact and dimension modeling approach
- Star schema and analytical modeling basics
- Business context preservation
- Reusable modeling strategies
- Creating graphical views
- Joins, unions, and projections
- Calculated columns and transformations
- Filters and aggregations
- Best practices for graphical modeling
- Introduction to SQL-based modeling
- Creating SQL views in SAP Datasphere
- Writing optimized SQL queries
- Using parameters and variables
- Comparing graphical views vs SQL views
- Defining business semantics
- Measures, attributes, and hierarchies
- Time-dependent data handling
- Currency and unit conversions
- Semantic consistency across models
- Creating analytical datasets
- Building analytical models for reporting
- Enabling models for analytics consumption
- Performance considerations for analytical models
- Model reuse across analytics tools
- Introduction to data flows
- Designing ETL/ELT logic
- Transformations and data cleansing
- Scheduling and monitoring data flows
- Error handling and data quality basics
- Role-based access control
- Object-level and space-level security
- Analytical privileges and data access control
- Managing users and permissions
- Best practices for secure modeling
- Modeling for high performance
- Data volume and partitioning strategies
- Optimization techniques for views and models
- Monitoring performance issues
- Governance and lifecycle management
- Connecting SAP Datasphere to SAC
- Live vs import connection scenarios
- Consuming models in SAC stories
- Best practices for end-user analytics
- End-to-end analytics flow
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SAP Datasphere Modeling Corporate Training Certification
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