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 Master Data Governance
Score 8.0 out of 10
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SAP Master Data Governance is a master data management solution that helps users to implement a cohesive and harmonized master data management strategy across all master data domains. It is presented as a solution that simplifies enterprise data management, increases data accuracy, and that facilitates consolidation, central governance and data quality management. The SAP Master Data Governance, cloud edition, a…
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Pricing
SAP Data Intelligence
SAP Master Data Governance
Editions & Modules
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No answers on this topic
Offerings
Pricing Offerings
SAP Data Intelligence
SAP Master Data Governance
Free Trial
Yes
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
Yes
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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More Pricing Information
Community Pulse
SAP Data Intelligence
SAP Master Data Governance
Considered Both Products
SAP Data Intelligence
Verified User
Former Employee
Chose SAP Data Intelligence
The extraction of data from the Source by creating SAP Data Intelligence Pipelines or Graphs and then updating in the Staging Table for the corresponding Migration Objects in the SAP Migration Cockpit. This process is really user friendly and easy to use with more efficiency …
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.
The best use case of SAP Master Data Governance is centrally consolidating your organizational data so you can make sense of it and make business decisions using that data. We live in a world where data can be all over the place, and making sense of it is a skill of its own.
Data conversation and Data uploading into SAP S/4 HANA system using SAP Master Data Governance during SAP implementation phase.
Centrally Data governance to have visibility of data in different systems with integration to SAP Master Data Governance, including SAP S/4, SAP EWM and SAP Ariba.
Data Management and Data correction using MDM through SAP Master Data Governance for Materials, which is subjected to approval before finally using in the S/4.
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.
We've had to design our own unique or alternative solutions to satisfy our business objectives because plugins don't always perform well with the main product.
It can be sluggish at times and lacks functionality offered by rival MDM packages, as well as limited resources and documentation for certain areas such as hierarchy.
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
MDG has proven to work and to bring results once implemented with the right approach, right engagement and sponsorship. Given that it is a very good tool to govern and control master data. Mainly if your company runs SAP systems which there will be a very straight forward integration, not needing any additional middleware or technologies.
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.
Upto 8 1. Powerful Features: It offers a wide range of powerful features. 2. Complex Data Management: It helps companies to comply with large and complex regulation and audit processes. Missing 2: 1. Less interactive user interface or less modern look. 2. Limited integration with other tools
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,
SAP provides great support for Master Data Governance (MDG). They work with us when we are faced with issues in standard solutions. SAP has a great set of Fiori tools that can be used for a better user experience. The issue with SAP is their web dynpro UI screens and they need to provide better support for performance issues that customers face.
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.
An environment provided by SAP Master Data Governance seamless and integration with other SAP products is very good. Also it ensures compatibility and streamlines procedures, this integration is beneficial for businesses who have already invested in SAP products.
MDG is definitely an investment that takes a few years to recuperate. (If you are looking at pure, direct financial benefits.)
However, if you look at all the productivity gains in the business due to not having to stop the business constantly because of data issues, the payback period would be substantially shorter.
In particular, we were able to reduce master data maintenance staffing levels while increasing quality and decreasing workload for business requesters and approvers.
Not having to worry about data integrity issues has shortened the time to realize benefits for several of our major process change related projects and it has also decreased the risk of these projects running into significant delays (often at the last minute) due to master data being misjudged during the process resdesign.
