Real-time in Datasphere
Data solutions must have a range of complementary capabilities to be effective. Data is a valuable resource for any business. They use data to make decisions and to make processes smarter and more efficient. Too often, however, organizations do not have the right data strategy in place. High-value data is often stored in silos and difficult to access. In addition, many SAP customers do not have the infrastructure to access their ERP data in real time. This makes it difficult to support use cases such as advanced real-time analytics and generative AI.
This is why SAP customers often turn to the experts at Confluent. Developed by the programmers behind Apache Kafka, Confluent's data streaming platform integrates directly with SAP Datasphere. It helps companies access their most valuable data within S/4 Hana and ERP/ECC 6.0, enabling downstream applications to be continuously fed with real-time data. Fully managed data streaming pipelines in the Confluent Cloud provide a continuous flow of data to every part of the business. Users have instant access to the information they need.
Confluent helps organizations modernize and overcome common challenges associated with legacy data architectures and data integration pipelines. For example, over time, custom integration patterns, such as point-to-point integrations, can slow down operations and impact an organization's ability to do business.
Not point-to-point
"A point-to-point integration strategy that merges all applications or data systems across the organization quickly creates a monolithic bird's nest. This stifles innovation, reduces customer satisfaction, and introduces unnecessary risk to the business," said Greg Murphy, Product Marketing Manager at Confluent. These legacy integration methods, which typically process data in batches, increase application or analytics latency.
In addition, larger organizations can experience a snowball effect, with more and more custom connections delaying operations. These delays can accumulate over time and significantly disrupt the company's day-to-day operations. Businesses cannot afford such risks. To meet customer expectations, they must process data streams in real time whenever possible.
Apache Kafka is at the heart of the Confluent platform. This open source data streaming technology empowers businesses with event-driven data to create real-time customer experiences. Used by more than 80 percent of the Fortune 100, Kafka is the de facto industry standard for data streaming technology. It enables companies to develop an elegant solution for real-time data needs.
By combining data streaming with real-time stream processing, companies can capture data points such as a sale or a shipment, collect information, aggregate it, put it in context, and retrieve it where it is needed.
Although Kafka is a widely used and very powerful data streaming technology, self-administration is a challenging, resource-intensive undertaking. It can take several years for companies to see a return on their investment. Confluent's data streaming platform is cloud-native, comprehensive, and available wherever it is needed. Confluent Cloud provides a fully managed Apache Kafka service based on the Kora engine, including elastic GBps scaling, unlimited storage, a 99.99 percent uptime SLA, highly predictable and low latency, and more—all while reducing the total cost of ownership (TCO) for Kafka by up to 60 percent. Confluent has completely redesigned Kafka's architecture for the cloud, so teams can spend more time innovating with real-time data and less time managing infrastructure.
Kafka and 120 connectors
In addition to cloud-native Kafka, Confluent provides all the tools needed to build real-time data products. Customers can deploy new use cases quickly, securely, and reliably. With Confluent, they work with a complete data streaming platform with 120 connectors, integrated stream processing with serverless Apache Flink, enterprise-grade security features, the industry's only fully managed governance suite for Kafka, out-of-the-box monitoring options, and more.
Confluent gives customers the flexibility to deploy data streaming workloads in the cloud (AWS, Azure, and Google Cloud), across clouds, on-premises, or in hybrid environments. Confluent is available wherever applications with clusters reside. They are synchronized in real time across environments to create a globally consistent central nervous system of real-time data that drives an enterprise.
Confluent has partnered with SAP to develop a direct integration with Datasphere to stream SAP data to the Confluent Cloud in real time, wherever it is needed. For SAP customers looking to enhance their data, Datasphere is one of the most important components. In fact, Datasphere is the center of gravity for customers because that's where all their data ends up. Applications that support real-time customer experiences and modern business processes/analytics require real-time access to SAP data. In addition, SAP data often needs to be merged with third-party sources, such as user clickstreams, to fully feed downstream applications.
"With this new integration, we are offering SAP customers the ability to power intelligent, real-time applications and analytics with their most valuable data residing in the SAP Business Data Fabric," said Greg Murphy. The combination of SAP Datasphere and Confluent's fully managed, cloud-native Kafka service enables users to build real-time applications at a lower cost. It serves as a central highway for real-time data, allowing SAP users to stream their data and merge it with third-party data in real time. Confluent provides more than 120 pre-built source and sink connectors. All of this is coupled with controls to meet stringent security, governance, and compliance standards. Confluent encrypts data both at rest and in transit to ensure proper protection.
Data is needed now. Companies can no longer wait until data is up to date. In an ever-changing economic climate, businesses must be able to respond immediately to market developments. Operating with high latencies not only has a negative impact on site traffic, but also on revenue that can be lost over the course of a year.
Data solutions must have a number of complementary capabilities to be effective. This includes connectors, stream processing, security tools, governance tools, and more. Companies should look for solutions like the Confluent Cloud that offer these options, are easy to install, and provide a holistic data solution. Cybersecurity should not be overlooked when making data management decisions. IT leaders should look for data management partners that prioritize security and privacy.
