SAP Data Intelligence is presented by the vendor as a single solution to innovate with data. It provides data-driven innovation in the cloud, on premise, and through BYOL deployments. It is described by the vendor as the new evolution of the company's data orchestration and management solution running on Kubernetes, released by SAP in 2017 to deal with big data and complex data orchestration working across distributed landscapes and processing engine.
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SAP Data Services
Score 8.8 out of 10
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SAP Data Services is an offering from SAP to improve data quality.
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SSIS
Score 7.6 out of 10
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Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
SAP Data Services offers more connectivity options without external connectors that must be purchased separately. Currently it has become a very robust platform with nothing to envy of its competitors, demonstrating very good results in all implementations. It handles many …
SAP Data Services is a very good tool and overall its easier to use than SSIS, but SAP is at a much higher price point than Microsoft. Microsoft can be a good fit for businesses of any size, but SAP tends to be a better fit for larger businesses.
These are all great products and, honestly, can move data faster. They include more enterprise features and have some great qualities about each. However, they all cost a lot depending on the implementation you need. With SQL Server Integration Services, you do not have any …
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.
It's definitely one of the leading ETL tools, and it's the best ETL tool to use with SAP integration. If you use SAP HANA, then you should think about Data Services as your primary ETL tool.
As I mentioned earlier SQL Server Integration Services is suitable if you want to manage data from different applications. It really helps in fetching the data and generating reports. Its automation make it very easy and time efficient. It works well with large database as well. But it doesn't work well with real time data, it will take some time to gather the real time data. I would not recommend using it in a real time/fast-paced environment.
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.
Connection managers for online data sources can be tricky to configure.
Performance tuning is an art form and trialing different data flow task options can be cumbersome. SSIS can do a better job of providing performance data including historical for monitoring.
Mapping destination using OLE DB command is difficult as destination columns are unnamed.
Excel or flat file connections are limited by version and type.
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
Some features should be revised or improved, some tools (using it with Visual Studio) of the toolbox should be less schematic and somewhat more flexible. Using for example, the CSV data import is still very old-fashioned and if the data format changes it requires a bit of manual labor to accept the new data structure
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.
SSIS is a great tool for most ETL needs. It has the 90% (or more) use cases covered and even in many of the use cases where it is not ideal SSIS can be extended via a .NET language to do the job well in a supportable way for almost any performance workload.
SQL Server Integration Services performance is dependent directly upon the resources provided to the system. In our environment, we allocated 6 nodes of 4 CPUs, 64GB each, running in parallel. Unfortunately, we had to ramp-up to such a robust environment to get the performance to where we needed it. Most of the reports are completed in a reasonable timeframe. However, in the case of slow running reports, it is often difficult if not impossible to cancel the report without killing the report instance or stopping the service.
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,
As other SAP products, there is excellent support by SAP on this tool. You can access the SAP Help portal in order to give support either from the huge community or directly from SAP.
The support, when necessary, is excellent. But beyond that, it is very rarely necessary because the user community is so large, vibrant and knowledgable, a simple Google query or forum question can answer almost everything you want to know. You can also get prewritten script tasks with a variety of functionality that saves a lot of time.
The implementation may be different in each case, it is important to properly analyze all the existing infrastructure to understand the kind of work needed, the type of software used and the compatibility between these, the features that you want to exploit, to understand what is possible and which ones require integration with third-party tools
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.
You cannot afford to run your business on questionable data. With SAP® Data Services software, you can access, transform, and connect data to fuel your critical business processes. Together, these enterprise-class solutions enable data integration and data quality, providing the right level of insight across your business so you can make better decisions and operate more effectively.SAP Data Services was previously known as SAP BusinessObjects Data Services, SAP BusinessObjects Data Integrator, BusinessObjects Data Integrator.
I think SQL Server Integration Services is better suited for on-premises data movement and ADF is more suited for the cloud. Though ADF has more connectors, SQL Server Integration Services is more robust and has better functionality just because it has been around much longer
Without this, we would have to manually update a spreadsheet of our SQL Server inventory
We would also have poor alerting; if an instance was down we wouldn't know until it was reported by a user
We only have one other person who uses SQL Server Integration Services , he's the expert. It would fall to me without him and I would not enjoy being responsible for it.