SAP Data Warehouse Cloud vs Snowflake

• With high in-memory speed, it is easy to analyze all sorts of data from unstructured to structured information.
• Preserving business context in a centralized location by connecting data from altered sources( cloud and on-premises repositories).
• Free customer support via multiple channels like E-mail, phone calls and live chat help in post implementation procedures.

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• This is a cloud-based application that provides me a secure platform for the easy sharing of data with my clients.
• I feel confident to connect with my numerous business partners just because of its advanced security and effective programming.
• Through this tool, I am capable of integrating, analyzing, and the entire data in a precise form and with analytics as well, due to which I always have a transparent idea about the data extraction and its transfer from multiple clouds.

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• SAP Data Warehouse Cloud is quite complex, therefore, some extra orientation or training might be essential, more so on cloud.
• Secondly, SAP Data installation fee, and the monthly subscription amounts is slightly demanding, and the developer should refocus on changing them.
• Nonetheless, SAP Data rectified other challenges like flexibility and customization, making us happy clients.

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• Snowflake UI can be clunky and breaks sometimes, which can be annoying
• Snowflake has to be paired with the Data Build Tool (DBT) to allow for templating and macro usage. No inbuilt solution.
• Snowflake Python connector development doesn't necessarily track popular packages such as Pandas as quickly as Pandas releases
• Could do with better machine learning capability over warehouse tables, but I assume this is coming soon

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• SAP Data offers special analytical results, understandable even by the end users.
• Also, SAP Data continues to bring ideals of a company together through collaboration and idea sharing, leading to innovation.
• Lastly, SAP Data cost of analysis, cloud storage, and safety is way below the installation costs.

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• Faster data retrieval makes real time analysis possible.
• Option to create multiple warehouses enable us to track usages and cost by departments.
• Option to scale up/down computational warehouse to support peak hours and month end loads makes Snowflake cost effective.
• Zero-copy cloning reduces storage and deployment cost.
• Multiple users can access the same amount of data without deadlocks which is a common scenario in relational databases.

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