CData Sync vs. SAP Data Intelligence

Evidently, CData Sync is an excellent middleware tool that is perfect for syncing data between systems. It is especially suitable and works well on SQL servers, DB2, MySQL, and Snowflake, and some of their brothering domains. However, it is a limitation in working with Sage 50 API. But if it is extracted with ODBC, it works well.

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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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• UPSERT
• Friendly interface

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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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• Although efficient for SQL servers and MySQL, as well as Snowflake. It is not strong for other database engines, and an upgrade on this would do a lot.
• The installation process is manual as opposed to the cloud installation it should be.
• A feature of syncing auto increment ID key, that will help in existing data management.

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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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It is easy to setup and use

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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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Tableau is another similar software tool, unlike CData Sync, rather transforms data into actionable insights. While CData Sync works with automation, Tableau uses a drag box on its AVA, which in turn slows the work speed on the syncing of data. Over the years, I enjoyed the friendly and customizable option of CData Sync over Tableau's.

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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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• Positive: Easy way to bring data for our DWH
• Negative: Frequent issue in CData Sync Server

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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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