Hybrid Architectures: A Modern Approach for SAP Data Integration

[florian_roeder]

Every business strives to get the most out of their data. The world of advanced analytics is creating newer, faster ways to interpret and apply data insights to business processes.

Challenge:

But the task of integrating SAP's central data warehousing solutions with third-party technologies was often perceived as complex and challenging. However, one of the most effective ways to manage data in today's environment might be through the concept of hybrid architectures. This approach combines the sophistication of on-premise and cloud data resources. It allows for a gradual modernization of data warehousing, with businesses leveraging historic data while reaping benefits from real-time analytics provided by cloud tools.

Hybrid architectures marry the best of both worlds, leveraging SAP's powerful data warehousing solutions like SAP Datasphere, and innovatively combining it with third-party technologies.

In the case of a German retailer, the following customized hybrid architecture was approached to cater to their data analytics needs.

Approach:

Here, along with internal SAP data, data from varying sources like e-commerce platforms, IoT devices, etc., is integrated and analyzed. In this hybrid system, the customer uses Snowflake for their central and strategic data warehousing / Big Data solution and Power BI for reporting, with the strategic decision-making data being stored securely in the SAP system known as SAP Datasphere. The central aim was to transition from classic on-premise BW installations while accommodating external data generated from various sources like e-commerce platforms and IoT devices.

Additionally, instead of an on-premise BW installation, the company decided to incorporate Power BI, Azure, and Snowflake for more scalable and flexible data handling. This integration of multiple platforms allows the retailer to optimize its data analytics process effectively.  

In response to this, SAP devised a target hybrid architecture that leveraged both Datasphere and BW Bridge, focusing on data integration and egresses valuation. The architecture is designed to facilitate the efficient transfer of SAP data into third-party systems. This was a staple feature that significantly made SAP's participation in data extraction lucrative. In other words, not only is SAP now responsible for the extraction of valuable SAP data, but it also monetizes this feature. 

Placed at the heart of these systems, SAP's Datasphere acts as an intermediary, managing data extraction, business semantics, and commercial data transactions. The system effectively handles both inbound and outbound data, keeping the process seamless and efficient.

In-bound data come from various SAP-centric sources systems and external data from Azure, which are then integrated with the Snowflake environment on Azure. The outbound perspective involves replicating the data physically from the transactional SAP systems into third-party data warehouses and hyperscaler technologies like Azure Data Lake Gen 2. This capability allows for a seamless transfer and synchronization of data between multiple platforms.

Further, the hybrid architecture model has helped SAP not just participate but also commercialize its data extraction process. Extracting data from these systems for third-party usage is now a means of revenue, preventing a potential loss of profit and ownership.

Hence, with the introduction of hybrid systems like these, businesses are now able to take full advantage of their SAP and third-party systems, ensuring data consistency, flexibility, and advancing their data and analytics capabilities. However, as mentioned earlier, implementation requires careful planning and considerable expertise to ensure seamless integration and utilization of these systems. Hybrid architectures further offer customers a flexible, cost-effective approach to modern data management. Businesses can optimally use data replication for real-time analytics, or data federation for reduced storage costs, bridging the gap between SAP and third-party systems like Snowflake, Azure, and Power BI. This increased efficiency and flexibility in data transfer allows businesses to harness advanced analytics capabilities, manage costs, and enhance performance.

Conclusion:

Hybrid architecture is thus an excellent model for organizations looking to maximize their data analytics capabilities while leveraging the best of SAP's powerhouse technology and other third-party applications. With robust inbound and outbound systems for data transfer, organizations can drive insights faster and more efficiently than ever before.