In order to use the data profitably to make the right decisions, you need a data warehouse that fits your requirements and with which you can react flexibly to changing demands. We would be happy to work out what this could look like together with you.
Design your own personal data warehouse architecture that is aligned with your goals – whether on-premise or in the cloud whether SAP or non-SAP or hybrid scenarios
Roadmap and project planning for your architecture change or upgrade
Selective data migration to your target architecture for minimum downtime and maximum security during implementation
Legally compliant decommissioning of your legacy BW systems using cost-effective and proven storage technology and with the help of SNP Glue™ as middleware for data outsourcing.
Takeover of system operation wherever it suits your requirements. Time, availability, systems, functions, remote or on-site, long or short term – everything is possible
Which data warehouse architecture best supports your corporate strategy in the long term and boosts the innovative ability and growth of your company? And how can you manage the transition to a new architecture – including the migration of your existing records?
We answer these questions for you in a strategy workshop. In this workshop, we first look at your current system landscape, and then, together with your team, we examine a number of essential decision criteria. These include technical requirements, such as the connection to existing data sources and the ability to integrate into your current application landscape. In addition, we clarify technical requirements with you such as desired analysis and visualization functions or collaboration options. In addition to these “hard” factors, we also include “soft” factors in our architecture recommendations, especially the existing tool know-how of your employees.
In this way, we ensure that your future data warehouse architecture not only meets technical requirements but that the selected tools are also accepted by employees and offer your company a noticeable return on investment.
As a further measure, we examine user behavior, data usage, and data growth in your current SAP BW system using our patented analysis procedure. These parameters are essential for the design of an innovative yet lean and cost-effective analytics architecture, and they enable us to plan your migration reliably.
As a result of the workshop, you will receive an architectural recommendation for your future data warehouse. This not only takes into account the area of SAP data but also other data sources and systems. On the other hand, you will receive a well-thought-out roadmap for the migration to the target architecture.
The specific design of your future data warehouse architecture depends on your individual situation and the planned application scenarios. However, the following three architecture variants are conceivable:
Pure SAP Architecture:
With this architecture, you rely on SAP technology throughout, from the back end to the front end. This includes the BW/4HANA Business Intelligence Suite and the SAP Analytics Cloud. This architecture variant is particularly recommended if you mainly work with SAP data and if there is no long-term need to evaluate data from external systems.
SAP + third-party architecture:
With this hybrid architecture option, your business data is loaded into SAP BW/4HANA for evaluation. In addition, you operate a corporate data lake for aggregating and evaluating mass data from other data sources such as sensor data from production or social media data. This type of data usually does not follow the SAP data model, and its half-life is usually short. Therefore, storing and evaluating data in SAP is neither practical nor cost-effective. A cloud-based data lake offers you more flexibility and moderate costs. The link between your SAP systems and the data lake is the SNP solution GLUE™. This solution automatically transfers relevant SAP data to the data lake, which you can then use to develop innovative applications in the area of automation and AI/ML. Of course, the whole process also works the other way around and without cumbersome or insecure workarounds.
Non-SAP:
Depending on the individual starting position, it may also make sense to set up a completely independent data warehouse. Platforms such as Microsoft Azure or Snowflake are usually used as backend technology.
Once your new architecture has been determined, we take over the data migration into your new data warehouse architecture for you. Our selective migration approach combines the advantages of the classic migration approaches greenfield or brownfield to a hybrid model. This means that you initiate a new start where it makes sense, cut off old habits which are no longer needed, and at the same time, retain the tried and tested habits.
"Completing work in the legacy system on Friday and starting seamlessly with the new data warehouse on Monday - our near zero downtime approach makes this possible without any problems."
Gregor Stoeckler
COO at SNP
It is based on a patented analytical method called HeatMap. We measure the use of your data and can distinguish little used data from frequently used data. Older and no longer actively used data, such as customizing and master data, as well as historical data make up about 80% of the system volume and are migrated weeks before go-live.
Current data such as recently loaded data or new queries, as well as changes to already migrated data are only transferred during the actual go-live. Through a precise measurement of your system and massive parallelization, even the largest systems can be migrated comfortably within one weekend.
You want to operate your data warehouse entirely or partially in the cloud? In this case, we can migrate your existing data warehouse in a Lift & Shift migration to a certified cloud solution such as Microsoft Azure.
Using a cloud as an analytics backend offers several advantages:
As independent experts, we are happy to advise you on the optimal architecture and, if required, take over the technical operation with certified experts for Microsoft Azure, Google Cloud, and AWS.
Development of corporate data lakes
By combining SAP data and process data from non-SAP systems in a corporate data lake, you can develop new, innovative applications in the field of digitization and automation. Examples are solutions for predictive maintenance of machines and IoT applications.
As the technical foundation for a corporate data lake, we recommend cloud platforms such as Microsoft Azure or Hadoop databases.
We advise you on the development of a corporate data lake and take over the technical implementation and migration of your existing data. With our own software solution SNP GLUE™ you can also connect your SAP systems to your data lake via a native and certified interface and automatically transfer transaction or master data to the cloud.
Automated data validation
A reporting system must also deliver the right figures after a system change. Therefore, there is no way around a thorough test. However, due to the considerable amount of time required and the monotony, testing is usually only half-hearted. In addition, the real test coverage and complexity in practice does not even come close to reality, which usually causes unpleasant surprises after the go-live.
Using our intelligent technology, we automate the creation of test cases as well as the execution by over 99%. Your migrated data and queries are thus automatically checked for completeness and correctness.
Your advantages:
