Master SAP HANA Cloud Data Modeling, Data Provisioning, Data Virtualization, Replication, Transformation, Performance Optimization, and Security to become a certified SAP Data Engineer.
English
Last updated
Sat, 24-Oct-2026
Becoming a Certified Data Engineer – SAP HANA Cloud is a comprehensive professional course designed for SAP Data Engineers, SAP HANA Developers, Database Engineers, Data Architects, BI Developers, Data Integration Consultants, Cloud Data Engineers, SAP Technology Consultants, and SAP certification candidates.
This learning journey provides end-to-end knowledge of SAP HANA Cloud data engineering, including data modeling, graphical Calculation Views, SQL development, data provisioning, virtualization, replication, transformation, project lifecycle management, performance optimization, security, and SAP HANA Cloud Knowledge Graph Engine.
By completing this course, learners will develop practical skills required to design, build, optimize, and manage enterprise-grade data solutions using SAP HANA Cloud.
Modern organizations rely on high-quality, integrated data to support business intelligence, analytics, artificial intelligence, and enterprise applications. SAP HANA Cloud provides a powerful cloud-native platform for data modeling, data integration, virtualization, transformation, and real-time analytics.
This course provides a complete learning journey covering SAP HANA Cloud Data Modeling and Data Provisioning. Learners will create graphical Calculation Views, implement SQL-based custom logic, optimize model performance, manage modeling projects, secure SAP HANA environments, create remote sources, virtualize enterprise data, replicate information across systems, and build transformation pipelines using Flowgraphs.
The course combines both development and administration concepts, enabling learners to become proficient SAP HANA Cloud Data Engineers while preparing for SAP certification.
Data modeling is the foundation of every successful SAP HANA Cloud implementation. This module introduces learners to the SAP HANA Cloud modeling environment and teaches how to design, develop, optimize, secure, and manage enterprise data models using graphical Calculation Views, SQL-based custom logic, and advanced modeling features.
Learners will gain hands-on knowledge of creating reusable, scalable, and high-performance data models that support reporting, analytics, and enterprise applications.
This unit introduces the SAP HANA Cloud modeling environment, including workspace preparation, project setup, modeling tools, development environment configuration, and prerequisites required before building enterprise data models.
This unit explains graphical Calculation Views and demonstrates how to create reusable semantic models that provide enterprise reporting and analytics capabilities while reducing SQL complexity.
This unit introduces the commonly used nodes available in graphical Calculation Views, enabling learners to manipulate, filter, aggregate, and transform enterprise datasets efficiently.
This unit explains how multiple enterprise datasets are combined using join operations. Learners will work with inner joins, left joins, referential joins, and optimize relationships between business datasets.
This unit focuses on combining multiple datasets using Union Nodes. Learners will understand schema alignment, data consolidation, and integrating information from multiple enterprise sources.
This unit explains data slicing techniques that enable users to create reusable filtered datasets for business-specific reporting and analytics.
This unit introduces ranking functions used for analytical reporting, enabling learners to identify top-performing products, customers, regions, or business transactions within enterprise datasets.
This unit focuses on embedding functions into Calculation Views to perform business calculations, derive values, manipulate data, and improve reporting capabilities.
This unit introduces dynamic Calculation Views that adapt to user input, filters, parameters, and runtime execution, enabling flexible enterprise reporting.
This unit explains hierarchical modeling techniques for representing organizational structures, product hierarchies, geographical structures, and business classifications.
This unit introduces SQL-based custom logic used within SAP HANA Cloud to implement advanced business rules, calculations, and data transformations beyond graphical modeling.
This unit explains industry best practices for creating scalable, maintainable, secure, and reusable SAP HANA Cloud data models that support enterprise analytics.
This unit introduces performance monitoring tools used to evaluate Calculation Views, identify bottlenecks, analyze query execution, and improve enterprise reporting performance.
This unit explains optimization techniques that improve Calculation View execution, reduce processing time, and increase scalability for enterprise workloads.
This unit focuses on techniques for storing Calculation View results to improve reporting efficiency, optimize query execution, and enhance application performance.
This unit introduces productivity tools that simplify model development, improve collaboration, and accelerate enterprise data modeling projects.
This unit explains how to organize development activities within SAP HANA Cloud modeling projects, including project structure, object management, and collaborative development.
This unit introduces project lifecycle management, including development, testing, deployment, maintenance, and version management of SAP HANA Cloud modeling projects.
This unit focuses on implementing security controls for SAP HANA Cloud models, including user authorization, object security, access control, and data protection.
This unit introduces the SAP HANA Cloud Knowledge Graph Engine and explains its role in managing relationships between interconnected business entities and datasets.
Data provisioning is a critical capability of SAP HANA Cloud that enables organizations to access, integrate, replicate, and transform data from multiple enterprise systems into a unified cloud platform. This module introduces the technologies and tools used for data virtualization, remote source configuration, virtual tables, replication services, and data transformation using Flowgraphs.
Learners will gain practical knowledge of integrating heterogeneous data sources while ensuring efficient, secure, and scalable enterprise data provisioning.
This unit introduces the core concepts of data provisioning within SAP HANA Cloud. Learners will understand how enterprise data from multiple systems can be accessed, integrated, synchronized, and prepared for analytics using SAP HANA Cloud technologies.
This unit focuses on data virtualization technologies that enable organizations to access remote data without physically copying it into SAP HANA Cloud. Learners will configure remote sources, create virtual tables, and understand virtualization architecture.
This unit explains data replication techniques used to synchronize enterprise data between source systems and SAP HANA Cloud. Learners will explore SQL-based replication, replication tasks, and replication services for maintaining consistent and up-to-date datasets.
This unit introduces data transformation techniques that prepare enterprise data for analytics and reporting. Learners will use Flowgraphs to cleanse, enrich, combine, and transform data from multiple enterprise sources.
This unit brings together the complete data provisioning lifecycle by demonstrating how virtualization, replication, and transformation work together within enterprise data engineering projects. Learners will understand governance, monitoring, and best practices for scalable SAP HANA Cloud implementations.
Throughout this course, learners will complete practical exercises using SAP HANA Cloud and SAP Business Application Studio to gain real-world experience in enterprise data engineering.
Participants will perform the following exercises:
In this capstone project, learners will design and implement a complete SAP HANA Cloud Data Engineering solution for a fictional enterprise. The project simulates real-world scenarios involving enterprise data modeling, multi-source integration, virtualization, replication, transformation, security, and performance optimization.
Participants will build scalable data models, provision enterprise data, optimize query performance, and create an integrated cloud-based data platform suitable for analytics and reporting.
Configure and implement:
Implement:
Configure:
Implement:
Upon successful completion of this project, learners will be able to:
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