SAP Business Technology Platform vs. SAP Data Intelligence

SAP Business Technology Platform is highly suitable for AI agentic development, particularly when workflows require dynamic orchestration, modular service integration, and real-time decisioning. However, it may be less effective in environments where backend services are fully encapsulated and do not expose interfaces or events that SAP Business Technology Platform can interact with—limiting its ability to orchestrate or extend those services meaningfully.

Incentivized

If you have an SAP products ecosystem in your IT landscape, it becomes a no-brainer to go ahead with an SAP Data Intelligence product for your data orchestration, data management, and advanced data analytics needs, such as data preparation for your AI/ML processes. It provides a seamless integration with other SAP products.

Incentivized

• Services are operated by SAP with outstanding support, always giving a helping hand even if it is custom code or solution provided on the platform
• Services are easily connectable via standard approach to our backend SAP systems in SAP Rise/HEC
• Secure access using identities from our existing identity management helping us to safeguard data security from within SAP systems up to custom frontend applications

Incentivized

• It integrates well with our current ecosystem of SAP products, like HANA.
• It provides end-to-end machine learning operations, with tools for the complete model life cycle.
• It has a simple user interface for novice users, with complex tools also available for power users.
• It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
• It can run in the cloud, no on-premise software management needed.
• Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
• SAP is very actively developing and improving it.

Incentivized

• For IAG, if there are multiple roles it can be overwhelming from an UX standpoint.
• Controlling and identifying shadow user creation is not as intuitive.
• Unlocking admin rights to an environment seems very easy if having elevated permissions, this seems like something that should have more controls rather than being able to unlock admin rights yourself.

Incentivized

• Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.

Incentivized

Seamless integration with external system and dashboard to monitor the data flow and analysis are very essential for the business. The way the product is designed and modelled lead to minimum business disruptions. Adopting to the new and modern technology was easy. Keeping the central system as clean and adopting project bases development are advantages.

Incentivized

Allow collaborations among various personas
with insights as ratings and comments on the
datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence

Incentivized

Okay, so the content that we have built on the platform is limited to specific testing on the iFlows within integration suite. The visualization layer is nice to use and helps with the design elements, however with developers that are more used to markup languages, it doesn't have the same CLI type feel when you want it. Perhaps the majority of users are that deep, but other platforms have a better CLI type developer experience.

Incentivized

I think the troubleshooting process might be streamlined with improved error recording and tracing. A lot of information about issues and how to fix them is hidden away in the Kubernetes pods themselves. I'm not sure whether SAP Data Intelligence can fix this problem it may be connected to Kubernetes's design, in which case fixing it could need modifications inside Kubernetes itself.

Incentivized

Services are generally available

Incentivized

The biggest problem we ran into was communication between SAP Business Technology Platform and onsite resources. Unfortunately our SAP Business Technology Platform and Cloud systems are under different customer numbers. I constantly had to open tickets under each customer number because I was unsure of where the issue lied. And having to create a dummy ticket for our ECC systems to open the ECC connections for another ticket under the Cloud customer is a pain.

Incentivized

Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,

Incentivized

Training material in Developers Community or from Learning hub are really good... also most of the time we route through Discovery center... so materials provided by SAP is really good.

Incentivized

Having a full cloud native environment for devlopment of microservices and digitals solutions while having standardized access to our core data on SAP via cloud connector is one of the main benefits of using BTP over others hypervisors. BTP is the standard hyperscaler as soon as something relies on data from SAP systems in our company now

Incentivized

Initially, SAP Business Technology Platform works hand in hand with S/4 HANA and the SAP product suite, but also can go and extra mile and integrate with other non-SAP products and services at hand. It's capable enough to understand the ERP use cases component and develop intelligent applications to satisfy the users.

Incentivized

One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.

Incentivized

It's scalable

Incentivized

• Still using traditional devops instead of using build. Very high cost in development.
• Still using Node.js instead of REST ABAP. Additional cost of resources. Migration of current CAP to RAP will be costly and do not have a business case yet. Continue with multi-language is costly.
• Integration suite is power but the migration from PIPO to IS has been more challenging than being advertised.

Incentivized

• Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
• Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
• It runs multiple ML models which enhances flexibility when managing data.

Incentivized