BigQuery Machine Learning
End of ECC 6.0 and R/3 and conversion to Hana and S/4 offers opportunities
A migration of the currently used database to Hana and a switch to S/4 is technically and probably also commercially inevitable in the medium term. It therefore makes sense to deal with the changeover in a timely manner. In terms of system operation, it looks as if there will be only one target platform in the future: the cloud. Among user companies, on-premises models still dominate - albeit with a declining trend - as well as hosting in external data centers.
SAP's public cloud is tailored to defined scenarios and plays a subordinate role in the consideration of most companies. SAP itself is pushing the switch to cloud-based products and services with Rise with SAP. In addition to the marketing pressure generated by SAP, other hyperscalers are naturally interested in taking on SAP workloads. Currently, seven hyperscalers offer certified IaaS platforms for OLAP and OLTP. For the German-speaking market, Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure are the relevant providers.
SAP operating models
The choice of operating model is based on a number of decision criteria such as security, regulatory conditions, controllability in operation, technical requirements, and service levels. It often happens that surprises arise in the course of the decision-making process when choosing the appropriate operating model. Supposed advantages and disadvantages are put into perspective when taking a closer look at the switch to the cloud, especially when it comes to security. The three hyperscalers mentioned, for example, offer their services in accordance with the Cloud Computing Compliance Controls Catalog (C5) of the German Federal Office for Information Security (BSI). C5 thus supports companies in proving operational security.
One aspect that is hardly ever considered in the initial approach and is also rarely taken into account in the bidding processes of the user companies is how a realignment of SAP operations affects the innovative strength and competitiveness of the user company. The fact that the future orientation of a core system of corporate value creation is rarely reflected in the catalog of criteria for awarding contracts is in any case remarkable.
Authority and agility
Likewise, new business models, such as direct-to-consumer services (DTC) and subscriptions, are becoming increasingly popular. The enterprise resource planning system will remain the central data storage unit (source of authority) in the future. In addition, hyperscalers provide database systems and technologies that enable companies to respond more efficiently and quickly to market demands (Source of Agility). The SAP Business Technology Platform (SAP BTP) provides the bridge to the transition in both worlds. For the hyperscalers mentioned above, SAP BTP is an established platform for connecting intelligent enterprise applications with database and data management, analysis, integration, and extension functions.
So what does this source of agility do? Google BigQuery, a serverless multi-cloud data warehouse for data-driven innovation in companies, is connected to the SAP ERP system via the BTP and serves as a system of agility. The data of the SAP system will be enriched with external datasets and streaming data in real time. BigQuery thus becomes the central solution for data analysts and data scientists.
Dataplex, an intelligent data fabric, gives organizations additional access to trusted data and helpful analytics at scale. They can centrally capture, manage, monitor, and deliver this data through data lakes, data warehouses, and data marts with unified controls. Next, they can leverage BigQuery's built-in machine learning (ML) to build and run machine learning models in BigQuery using standard SQL queries.
Machine learning with large datasets requires extensive programming and ML frameworks skills. These requirements limit solution development in most companies to a small group of people. Data analysts are not one of them because while they understand the data, their programming skills and machine learning knowledge are often limited. With BigQuery Machine Learning, data analysts don't need new knowledge and can use existing SQL tools to leverage machine learning. This allows the SAP operations team to take care of their tasks - meanwhile, the customer-facing units have access to highly aggregated and visualized real-time data to make the right decisions.
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