DemandTools vs. SAP Data Intelligence

DemandTools is good for almost everything related to mass data manipulation. The only scenario I haven't tried using DemandTools and was recommended to use Data Loader for was inserting records while keeping the original created date. The issue was that we had a disconnection with an external messaging partner, and when the records were retrieved, a few days had passed since the original day of the incoming messages. To insert the messages while keeping the original created date, DataLoader was helpful. I am not sure how to do that in DemandTools. But again, for everything else, DemandTools is a lifesaver.

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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.

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• PowerGrid can review and make the updates simultaneously.
• Single Table Dedupe makes merg[ing] the records easy and can make updates at the same time.
• BulkBackup [is] just one click, majority data got updated.
• Scenarios save a lot of time for similar working load.

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• 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.

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• I wish I could make changes to my existing scenarios using save rather than having to create a whole new scenario. Maybe you can, I just haven't been able to.
• Some features aren't user intuitive and it takes a while to learn.

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• 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.

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It's a great product. The only thing that holds us back is it was frustrating working with their sales team. We also don't like that when Validity purchased DemandTools they immediately started charging us quite a bit while it had been free for non-profit users when CRMFusion owned it. They also don't let you buy it for just 1 or 2 seats, you have to pay, I believe, in batches of 100 seats.

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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

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Allows for control in uploading lists, saved processes for checking duplicate records.

Allows for backup files and quick reverts if something goes wrong.

Extends reporting when Salesforce.com cannot support specific pieces of info being put together in a report.

Automated processes for set and forget hygiene tasks

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.

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There has not been a time since I started 9 months ago that I've encountered any kind of downtime.

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DemandTools is a bit clunky and slow at times

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Support can be slow so do not expect quick turn for urgent issues.
Help for specific queries not not there. Product tech support is offered. It would be great if query support, even if paid, was offered
The training webinars help with the basics but not much if you need advanced functionality.

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,

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The trainings are free live webinars that give you a solid base for getting started with the program. The only weakness is they don't have any advanced classes.

I had just started using Salesforce about 3 months before I did the implementation myself, and it was easy to do just following their step-by-step instructions.

Though RingLead has much more to offer in terms of automation (and it is in Salesforce rather than a separate program), DemandTools still has our heart. DemandTools is very cost-friendly and we were able to increase the value of DemandTools by programming in additional saved scenarios. I decreased admin time in the DemandTools suite by approximately 25% after implementing saved scenarios for every reoccurring update or list upload.

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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.

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It's done everything we've needed it to do.

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• It is a tremendous time saver. It does things Salesforce doesn't even have the capability to do. Tasks that would take hours to manually complete.
• We can process a tremendous amount of data daily through one person, vs. weeks for the data to be cleaned, reviewed, routed and input.
• Saves on headcount by allowing a dedicated user to set up batches and jobs for other teams to ensure their data integrity.
• The return on investment isn't easily quantifiable but it is FELT in our department.

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• 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.

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