CData DBAmp vs. SAP Data Intelligence

Well suited as an inexpensive tool as "middleware" between your on-prem or hosted SQL Server. Not sure how well it will translate to cloud-based SQL as a platform (Azure SQL) as it relies on linked servers. This tool only applies to Salesforce CRM - not Marketing Cloud. For writing back to Salesforce we did run into Salesforce resource limitations when extensive triggers existed on the objects.

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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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• Connects & Links to Salesforce CRM databases - including custom objects.
• Built in procedures to create copies of the database on SQL Server.
• Built in procedures to Add, Update, and Delete data within Salesforce CRM.
• Great Technical Support.

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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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• Because it uses Linked Servers, not sure how this will work in Azure SQL.
• Replicated tables are based on user security - this means you have to pay for a license to set this up.
• There is no built-in function to skip tables or fields on secured tables. This has to be done on the CRM side for fields and we built a function to skip tables in the replication logic.

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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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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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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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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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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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• Enabled automated marketing segments which enabled automated email series.
• Helped us solicit donations for the right amount at the right time.
• Helped us take on new marketing and fundraising campaigns without adding staff.

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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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