Choosing a Data Modeling Solution


After completing this lesson, you will be able to:

  • Choose the correct data modeling solution based on the requirements of the business

Comparison of the Modeling Solutions

This SAP Learning Journey has introduced you to the various data modeling solutions from SAP. Now you are ready to contribute in discussions with SAP experts.

SAP provides various solutions to support data modeling. Each solution provides a common set of data modeling capabilities. But each solution also has its own unique additional capabilities. So how do you choose the right one?

Selecting a tool is a challenge for many organizations who are building analytical applications and need tools to turn their huge stores of jumbled-up, raw data into useable business intelligence.

There are many factors to consider when choosing a data modeling solution. These include: the source of the raw data, the intended consumption of the data, the platforms that are implemented, whether data warehousing capabilities are needed, the existing skills of your team, and whether you are looking at a cloud or on-premise solution. In some cases, there's more than one choice that would fit. But we can say there's usually one optimal solution for every scenario which ticks the boxes of most, if not all of the requirements.

So, to help you make the choice, we have summarized the key strengths of each solution and provided a typical scenario where it fits. The intention is to help you compare one solution against the others, at a high level. As always, detailed analysis of the requirements is needed to find the right solution but this lesson should help.

Modeling using SAP HANA Calculation Views

Modeling with SAP HANA calculation views has the following strengths:

  • Data processing is always performed in memory in the database, which results in high performance.
  • The graphical user interface is easy to use and provides a substantial set of data modeling capabilities.
  • You can add SQL to your calculation views to provide additional, custom logic.
  • Same skill set for cloud and on-premise SAP HANA deployments
  • Advanced analytical features such as spatial, graph, text analytics and predictive / machine learning.

SAP HANA calculation view modeling is a good choice for developing flexible data marts, especially when you want to include custom SQL into the development. Also, calculation view modeling tools are included in SAP HANA. This means if you are running an SAP application that run on the SAP HANA database, you already have access to modeling tools (subject to software license conditions). But with no ready-made models supplied, there is potentially a lot of effort to develop your data models from scratch. Also, if you are looking for in-built, data warehouse capabilities, you would have to build these yourself using SQL.

Modeling using SAP BW/4HANA

Modeling with SAP BW/4HANA modeling has the following strengths:

  • SAP provides comprehensive, ready-made data models to support virtual access and physical storage, with built-in connectivity (data extractors) from most SAP sources, including SAP ERP and SAP S/4HANA and SAP SuccessFactors.
  • SAP BW/4HANA supports typical data warehouse requirements e.g. dimensional modeling, star schemas, data historization, hierarchies, harmonization of data from different sources, efficient data storage using temperatures.
  • All core modeling features are provided by a graphical tool that is designed for easy visualization of models and high productivity.
  • You can develop customizations using ABAP.
  • On premise provides a good option for customers who work in an industry that requires very high levels of security e.g. banking, defense, public sector, that do not work with public, cloud-based solutions.
  • On-premise deployment means customers owns the solution and has full control of software updates, down-time etc.

Customers choose SAP BW/4HANA because they want to build an on-premise data warehouse. They want to manage their data history from a large number of SAP and non-SAP sources, where strong data integration capabilities are important. They usually already have SAP solutions in place, such as Business Suite or S/4HANA and want to take advantage of the significant, ready-to-go content that is provided for those solutions.

Modeling using ABAP CDS Views

Modeling using ABAP CDS views has the following major strengths:

  • Pushes down all data processing into the database to ensure high performance.
  • For SAP S/4HANA, SAP provides sophisticated, ready-made data models for virtual access and live reporting.
  • Very flexible code-based development leveraging SQL skills

If you run SAP S/4HANA, choosing this modeling approach is an easy choice. The tools are already included, and actually the content is ready-made so it's easy to get started with live, operational reporting on SAP S/4HANA. but if you have other data sources that should be integrated into the data model, then this solution is probably not enough. Also, using ABAP CDS views is probably not the best solution for building a data warehouse where you need sophisticated data historization management.

SAP Analytics Cloud modeling

Modeling with SAP Analytics Cloud has the following major strengths:

  • Modeling integrated with the reporting tools means a single environment and self service for business users
  • Cloud service, so no need to run the software, just consume it.

Modeling with SAP Analytics Cloud brings data modeling close to the frond-end tools. This means that business users can develop their own data models whilst working on the visualization. However, this approach doesn't provide the advanced data modeling tools compared to the other solutions. There are no data warehousing capabilities such as data historization, load monitoring and delta extraction. Many customers using SAP Analytics Cloud prefer to consume models that are managed centrally, for example using SAP Datasphere or SAP BW/4HANA. Modeling with SAP Analytics Cloud can result in the development of individual models that are not shared with others across the organization .

SAP Datasphere

Modeling with SAP Datasphere has the following major strengths:

  • SAP Datasphere supports common data warehouse features such as dimensional modeling, data history management, hierarchy modeling, harmonization of data from different sources.
  • Data processing works in memory at database level in all cases with fast processing speed.
  • You can easily scale the system and allocate system resources (memory, CPU).
  • Support for new innovations because cloud solutions typically receive new features before on-premise.
  • Easy switching between remote (virtual) access and replication (physical data load and store)
  • It is a cloud service so no need to run the software, just consume it.

If you want a data warehouse in the cloud, SAP Datasphere is probably the right choice.

SAP BusinessObjects BI Semantic Layer (Universes)

Modeling with the SAP BusinessObjects BI Semantic Layer has the following major strengths:

  • Easy to use graphical tool to develop data models
  • SQL based, so its easy to understand by database developers.
  • Mature tool with a very large feature set

The most common scenario for choosing to model using SAP BusinessObjects BI Semantic Layer is that you run Web Intelligence or other SAP BusinessObjects reporting tools that already make use of Universes.

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