Data Science and SAP BTP – a perfect fit?
Is SAP BTP really the best choice for implementing machine learning (ML) models? Our Data Science team is absolutely convinced. Why? Alina Meiseberg, Senior Data Scientist at sovanta, tells us. She summarizes the benefits, tools and features on SAP BTP that optimize and accelerate ML development.
So far still an ML underdog: The SAP BTP
For me as a Data Scientist, it is crucial to use a reliable and secure platform to develop and deploy Machine Learning models. But now there are more and more platforms to develop, deploy & manage ML models. At sovanta, we have worked on many different platforms, such as Databricks, Azure with Kubernetes and co. There is one solution that tends to be overlooked: The SAP Business Technology Platform (SAP BTP). SAP BTP offers many options for carrying out ML projects and also numerous tools and services for integration. Here are three advantages of working on the SAP BTP that are decisive for me:
Advantage 1: Deeply integrated into SAP systems
SAP BTP is a cloud-based platform that provides a variety of services and tools for application development and deployment. A key differentiator of SAP BTP compared to other cloud providers such as AWS and Azure is its specific focus on business-critical applications and specifically applications built on SAP systems. SAP BTP offers extensive integration with SAP systems, which enables companies to optimize and automate their existing business processes. That’s why SAP BTP lends itself simply well to data science projects that integrate deeply with business processes.
Advantage 2: Data security is clarified
In addition, SAP BTP also provides a high level of security to ensure the confidentiality and integrity of data and applications. Companies can be confident that their data and applications are secure and that their compliance and data protection requirements are met. This immensely facilitates access to data needed for model retraining or predictions – as data security is no longer an obstacle.
Advantage 3: Tools to scale
SAP BTP is also an ideal working environment for Data Scientists as it offers a wide range of tools, such as SAP Data Intelligence and SAP Datasphere, as well as functions for working with data and creating or cataloging AI models. Thanks to SAP AI Core, ML models can also be easily scaled. This makes it possible to keep pace with growing data volumes and requirements.
That was already exciting?
There is a lot of movement in this area at SAP right now. Just recently, there was a big announcement: The previous product SAP Data Warehouse Cloud was renamed SAP Datasphere and is to be the central point of contact for data in SAP from now on. This again opens up new opportunities in the field of data engineering. Feel free to contact me directly for a deeper exchange.