Course Summary

Advanced data analysis and processing workloads require much more than a tabular data store and standard aggregation of numerical data. To provide complimentary capabilities like full-text search, machine learning, spatial processing, and network analysis, some project teams have assembled a quite complex system landscape with point solutions for each specific task. This leads to massive challenges in data replication, authorizations, and query federation, and high costs for system operations and development workflows. With the multi-model features in SAP HANA Cloud, you can tackle these challenges and build intelligent data apps.

SAP HANA Cloud is a modern database as a service (DBaaS) powering the next generation of applications across all enterprise data. It supports data and analytics at scale with one solution and enables intelligent data applications by embedding machine learning and data science, supporting advanced geo-spatial analysis, native full-text search, in-database graph processing, and many more multi-model capabilities.

This course focuses on SAP HANA Cloud and is aimed at software developers ready to learn about less well-known SAP HANA capabilities. In this course you’ll get an introduction to multi-model features, including the Document Store and working with JSON data, the Spatial engine and processing geo-referenced data, as well as the Graph engine and analyzing connected data. You’ll also learn how these capabilities can be combined to power an intelligent data app that enables a site selection scenario for new electric vehicle charging stations.

Course Characteristics

• Starting from: November 6, 2023, 09:00 UTC. (What does this mean?)
• Duration: The course is open for 4 weeks
• Effort: 3-4 hours in total
• Course assignment: You can take the course assignment at any time whilst the course is open.
• Course closure: December 5, 2023, 9:00 UTC
• Course language: English
• How is an openSAP course structured?

Course Content

Unit 1: Course overview and introduction
Unit 2: Managing data in SAP HANA Cloud
Unit 3: Working with geo-referenced data
Unit 4: Leveraging full-text search
Unit 5: Analyzing connected data
Unit 6: Utilizing machine learning
Unit 7: Building intelligent data apps

Target Audience

Application developers

Course Requirements

Basic understanding of relational database management systems and SQL

Development Systems

If you are interested in exploring the multi-model capabilities of SAP HANA Cloud and developing your own code based on the course content, you can sign up for the free tier model for SAP BTP.

Further Learning

SAP HANA Multi-Model Community resources:
https://community.sap.com/topics/hana/intelligent-data-applications
https://blogs.sap.com/2021/07/21/sap-hana-graph-resources/
https://blogs.sap.com/2020/11/02/sap-hana-spatial-resources-reloaded/

SAP HANA Cloud tutorials, e.g. :

https://developers.sap.com/tutorials/hana-trial-advanced-analytics.html
https://developers.sap.com/group.hana-aa-graph-overview.html
https://developers.sap.com/group.hana-aa-spatial-get-started.html
https://developers.sap.com/group.hana-cloud-database-python-multi-model.html
https://developers.sap.com/group.hana-cloud-smart-multi-model-data.html
https://github.com/SAP-samples/teched2023-DA285v/tree/main

About Further Content Experts

Christoph Morgen

Christoph Morgen leads SAP HANA Product Management for Machine Learning, supporting the development teams and driving the innovation of the Predictive Analysis Library, open source integration, machine learning clients for R and Python and the integration and use of HANA Machine Learning functions within SAP applications to enable the Intelligent Enterprise. 

Christoph has been with SAP in SAP HANA product management roles for over 10 years and has over 24 years of advanced analytics industry experience in solution management, pre-sales, education, and consulting. Consequently, he has always been in close contact and collaboration with partners and customers, supporting them on their path to success.

Christoph holds a diploma in Landscape Ecology from the University of Münster, where his machine learning journey began with multivariate statistics and regression analysis.

Follow Christoph Morgen on LinkedIn

Mathias Kemeter

Mathias Kemeter is a development manager for SAP HANA. His focus is on multi-model processing, which includes SAP HANA’s spatial engine, graph engine, and the JSON document store.

Mathias is active on SAP Community and publishes blogs on his favorite projects and topics, which usually combine a pinch of data science and advanced analytics with vast amounts of multi-model data.

Follow Mathias on SAP Community | LinkedIn | Twitter