According to Forrester, between 60% and 73% of all data within an enterprise goes unused for analytics. And with SAP touching more than 77% of the world’s transaction revenue, it is hardly surprising that many organizations face a major gap between their SAP data and their data driven goals!
Advanced analytics, innovation, and democratization of SAP data to collaborating teams is difficult, due to the complexity of the data as well as the inherent limitations of integration with your SAP investment.
We understand that our customers want to react early and make fast, precise, and impactful decisions and they want to use the best of breed technologies.
With SNP Glue we offer simple SAP certified data integration and data products compatible with all the major innovative platforms and targets, including Microsoft Azure, Amazon Web Services, Google Cloud Platform, Snowflake, etc.
With our SNP GlueTM software solution, we offer certified middleware for integrating your SAP systems with data platforms such as Microsoft Azure, AWS, Cloudera, and Google Cloud Platform. Thanks to the bi-directional SAP interface, you can transfer SAP data securely and conveniently to other platforms (such as data lakes), or load data from non-SAP systems into your SAP landscape.
The core of SNP GlueTM is the SAP Data Products Catalog. It allows your users to choose the data they need from a repository of hundreds of SAP data objects, and can easily define exciting integration scenarios.
To ensure that your employees can quickly find their way around the catalog, we have designed the user interface to be particularly straightforward. It can be easily used by anyone without SAP experience.
Get data out of SAP and into your modern data warehouse and, better still, use it for analytics, data science or to fuel innovation in general. With our SAP certified interface, you can integrate your SAP data seamlessly into any platform and develop innovative applications with AI / ML and IoT – accelerating the time to value. We have selected some particularly interesting application examples from our extensive library of demo scenarios for you and present them in more detail below:
Big data can help you better understand your customers and target sales activities to your best customers. To do this, however, you need a uniform and complete view of all customer data. But in practice, customer-relevant data is usually scattered across many systems that do not communicate with each other.
You can solve this problem by consolidating all customer-related transactions and master data in one data lake. For example, your SAP systems can provide data on sales, pricing conditions, payment history, and returns. Your CRM and call center applications, in turn, deliver information on support requests or complaints from your customers. Using a data lake, you can evaluate this data in a consolidated form, aggregate it and present it as KPIs in a dashboard for your employees.
Unplanned breakdowns of machines, vehicles, or other equipment disrupt the operating process and cause major additional costs. Predictive maintenance can help you avoid such failures.
You can set up predictive maintenance with the following steps. First, set up a transfer path to be able to transfer current sensor data from machines or components under consideration to a data lake. Next, machine learning algorithms are set up and trained. You can recognize an imminent component failure at an early stage based on suspicious patterns in the sensor data. If a component threatens to fail, a maintenance order can be created automatically in SAP to initiate maintenance tasks. The repair can now be planned, and more considerable damage due to an unexpected total failure is avoided.
