SAP Data Intelligence vs. SAP Integration Suite

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

Good at: 1. Integrations with in SAP applications, especially with event based triggers 2. Can be integrated very well with other BTP services to attain Batch processing and store credentials 3. Supports many authentication models Improvements: 1. No version history available compared to as it is available in S4HANA 2. Need a lot of improvement in git hub connections

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

• The extensive catalog of pre package integrations that have in the discovery center. That allows developers to find solutions that can fit the needs.
• Monitor of the integrations and api deployed.
• API management has been for us a very usefull tool inside integration suite, to be able to have the API Hub with the documentation of our apis.

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

• Provide more pre-built integrations to use within SuccessFactors or other modules instead of everything having to be custom built
• Support is unable to provide advice on custom builds so you often have to engage a 3rd party partner
• Works best when you have the functional and technical teams working together. Otherwise, the system is too technical for a functional user to create integration and a technical user not always understand the functional perspective

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

It is in place, our system integrators are familiar with it, and it fits into the ecosystem. A better user interface, flow build and debugging experience would see it grow, many technical staff do not enjoy using it for this reason, however it is quite capable and powerful behind this one shortcoming.

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

The user interface is messy and not intuitive. It has a steep learning curve, and flows developed around are easy to make a mess with layout and can be difficult to follow. The debugging is also quite difficult, it takes some time to figure out how to follow the flow and examine data. Error handling is also difficult and not intuitive, it is better to let some errors leak and monitor through ALM.

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

The support for SAP Integration Suite is satisfactory. We leverage SAP support through our manage services partner. So far, we have not had many major issues. One concern, to make our rating a ten, would be turnaround time on high priority incidents. SAP Integration Suite drives our key business functions forward. Without a reasonable service level agreement on turnaround, we sometimes find us running into issues running pay, etc.

Incentivized

Work with an SAP implementation partner, if possible.

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

Before deploying SAP Integration Suite, we assessed Oracle Financial Services Analytics and IBM Risk Analytics. While Oracle had proved its mettle in the exceptional database support and IBM in presenting risk model tools, SAP Integration Suite overwhelmed others by being effortlessly integrated with our existing banking framework.

• 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

• Positive impact would be availability of pre-defined integration content via templates.
• One can re-use a template as a starting point to modify and adopt to client-specific integration flow.
• Availability of adaptors and connectors, making it easier to piece together the integration flow.

Incentivized