SAP Datasphere

Data Modelling SAP Datasphere

Data models can be created in SAP Datasphere and then analysed in SAP Analytics Cloud. Model creation, data visualisation, and data analysis are the focus of this teaching and learning environment. For this purpose, students learn how to use Data Builder and Story Builder. Students will learn how data is analysed and how business decisions are made based on that data

SAP IBP Key Features

Cloud-Based Data Modelling

SAP Datasphere is a powerful platform capable of collecting, processing, and integrating data from a wide variety of sources. The flexibility to handle both structured and unstructured data, as well as information from SAP and non-SAP systems, makes it an extremely versatile tool.

Advanced Analysis and Visualisation

For data analysis and visualisation, SAP Datashere can also be integrated with SAP Analytics Cloud to transform data into meaningful insights. These insights provide companies with valuable information that can support them in making strategic decisions.

New Analytic Model

With this new function, it is possible to derive any number of analytical models from a flat fact table for later evaluation. A content preview of the facts and dimensions as well as an OLAP analysis are possible directly in SAP Datasphere. Each of these different analytical models based on the same fact table can be evaluated in detail in external data analysis and visualisation tools such as SAP Analytics Cloud.

Data Modelling in SAP Datasphere in Your Teaching

ESEFA provides access to the SAP Datasphere cloud environment for data modeling. For subsequent data visualisation, the SAP Analytics Cloud is integrated. A total of up to 100 students can access the learning environment simultaneously. Lecturers have access to teaching materials, such as ready-to-use presentations, exercises, and case studies that can be used both in teaching and in research projects.

The entire curriculum is available only available in English.

Learning Objectives

Introduction to cloud native data warehousing

Understand difference between classic and cloud data warehouse solutions

Model data warehouse and load data from flat files

Merge heterogeneous data of different companies

Prepare insights for data visualisation