Regardless of the business sector, every organization has one resource that they desperately need – data. Companies use data to guide their decision-making and enhance their operations to be more intelligent and efficient. Yet all too often, companies do not have the underlying data strategy that allows them to extract crucial real-time insights. Frequently, high-value data is sitting within data stores and silos all throughout the business, making it difficult to access. Additionally, many SAP customers don't have the infrastructure in place that allows them to access their ERP data in real-time to power use cases like modern, real-time analytics and GenAI. Many SAP users that find themselves in this situation are turning to the data streaming experts at Confluent to address the challenge. Built by the original creators of Apache Kafka and directly integrated with SAP Datasphere, Confluent’s data streaming platform helps companies access their most valuable data within SAP S/4HANA and ECC to fuel downstream applications with a continuous supply of real-time data. Fully managed data streaming pipelines built on Confluent Cloud provide ongoing flows of data to any part of an organization, allowing users to immediately access and utilize the information they need the moment they need it.

Addressing Pipeline Issues

Confluent helps organizations modernize and overcome the common challenges tied to legacy data architectures and data integration pipelines. For example, an architecture of point-to-point integrations where every application is uniquely integrated with every single data source, etc. Over time, these custom integrations patterns can slow down operations and harm an enterprise’s ability to do business. “A point-to-point integration strategy stitching together every application or data system throughout the business quickly creates a monolithic bird's nest that blocks innovation, harms customer satisfaction, and introduces unnecessary risk to the business,” said Greg Murphy, Product Marketing Manager at Confluent. Typically moving data in batches, these legacy integration methods increase application or analytics latency. Additionally, larger businesses can experience a snowball effect where more and more bespoke connections can seriously delay operations. These delays can build over time and significantly hamper an organization’s day-to-day operations. Organizations cannot afford risks of this type with their data and must look to process streams of data in real-time to meet the expectations of today’s customers. At the center of Confluent’s platform is Apache Kafka, an open-source data streaming technology that provides businesses with the event-based data necessary to build real-time customer experiences. Used by more than 80% of the Fortune 100, Kafka is the de facto standard data streaming technology within the industry. It allows users to develop an elegant solution for real-time data needs across a business. Data streaming—paired with real-time stream processing— affords businesses the ability to capture data points like a sale or a shipment, collect all the information, bring them together, merge them, give them proper context, and move them downstream to every location where they need to be.

Confluent’s Data Streaming Platform

While Kafka is a widely adopted and highly powerful data streaming technology, self-managing it is a challenging, resource-intensive effort that can take multiple years to realize major value for a business. Conversely, Confluent’s data streaming platform is cloud native, complete, and readily available everywhere it’s needed:

• Cloud Native – Confluent Cloud provides a fully managed Apache Kafka service powered by the Kora Engine including GBps+ elastic scaling, infinite storage, a 99.99% uptime SLA, highly predictable/low latency performance, and more—all while lowering the total cost of ownership (TCO) for Kafka by up to 60%.Confluent completely re-architected Kafka for the cloud—allowing teams to spend more time innovating with real-time data and less time focused on infrastructure management.
• Complete – Alongside cloud-native Kafka, Confluent provides all the tools necessary to build real-time data products. Customers deploy new use cases quickly, securely, and reliably when working with a complete data streaming platform with 120+ connectors, built-in stream processing with serverless Apache Flink, enterprise-grade security controls, the industry’s only fully managed governance suite for Kafka, pre-built monitoring options, and more.
• Everywhere – With Confluent, customers can maintain deployment flexibility for data streaming workloads by running in the cloud (AWS/Azure/Google Cloud), across clouds, on-premises, or in a hybrid environment. Confluent is available wherever applications reside with clusters that sync in real time across environments to create a globally consistent central nervous system of real-time data to fuel a business.

Customer Success Story

Confluent recently helped payments processing organization Flow Networks overcome significant challenges. The company wanted to build a real-time payment processing platform to enable contextual and personalized customer engagement. Flow realized it needed an event-driven architectural foundation to manage this. Flow needed nodularity in its solution, so its domain could be reduced to smaller parts and then connected back. It also required the scalability to grow and the flexibility to pivot strategies. Flow reached out to Confluent Cloud to act as its backbone, powering its B2B2C payments platform. By leveraging AWS and Confluent Cloud, Flow is now able to add context to data so it can provide real-time recommendations to merchants and customers for the next best action following a transaction. Confluent also provides Flow with much-needed scalability so it can grow its data pipelines while still having the speed and agility to enrich payment data in real time. While all these components are important, perhaps no aspect of data streaming is more important than privacy when it comes to financial transactions. Since it handles sensitive data from banks and individuals every day, Flow appreciated that Confluent provides a single source of truth for all data, as well as a full suite of enterprise-grade security controls including the ability to protect data privacy using audit logs on streams without losing analytical strength.

SAP Relationship

For SAP organizations working to enhance their data, SAP Datasphere is perhaps the most essential piece of that puzzle. SAP Datasphere effectively serves as the main point of gravity for its customers, as that is where all their data will land. However, it is not the end state for that data. The data needs to move downstream so it can be placed within the applications that are going to power customer experiences and business operations/analytics in real-time. Additionally, data from SAP needs to be merged with third-party sources like user click streams to comprehensively hydrate downstream applications. Confluent worked with SAP to develop a direct integration with Datasphere to stream SAP data into Confluent Cloud for real-time distribution everywhere it needs to go. “With this new integration, what we're providing SAP customers is the ability to fuel intelligent, real-time applications and analytics with their most valuable data residing within the SAP business data fabric,” said Murphy. The combination of SAP Datasphere with Confluent’s fully managed, cloud-native Kafka service allows users to build real-time applications at a lower cost. Serving as a centralized highway for real-time data, it also allows SAP users to stream their data and merge it with third-party data in real-time, as Confluent provides more than 120 pre-built source and sink connectors. This all comes with controls to maintain strict security, governance, and compliance standards. Confluent encrypts data both at rest and in flight to ensure that it is properly secured.

What this Means for SAPinsiders

Data is needed now. Organizations can no longer wait for data that is not fresh. In an ever-shifting economic reality, businesses need to react to market forces immediately. Operating with high-latency also negatively impacts businesses in terms of the amount of traffic that will stay on the site and the amount of revenue that can be lost over the course of a year. Leverage complete solutions. Data solutions need to have an entire suite of complementary features in order to be effective. These include connectors, stream processing, security tools, governance tools, and more. Organizations should seek out solutions like Confluent Cloud that offer these options that can be easily installed and provide a holistic data solution. Protect Data Privacy. Cybersecurity cannot be lost among the other considerations that companies should make in their data management decision. IT leaders should seek out data management partners that prioritize security and privacy.