Transactional Databases are optimized for... Operational Workflows Machine Learning Analytics Transactional Databases are optimized for... Operational Workflows Machine Learning Analytics
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Which of the following are characteristics of transactional (OLTP) databases? Good to use for storing "add to cart" items Designed for fast processing Typically has normalized data All of the above
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4. What kind of data do I need to analyze? Is the majority of your company’s data transactional? Is it all structured? If so, a traditional or “legacy” tool may be the best fit for your use case. If the bulk of your data streams to your data lake in real-time via CRM, cloud applications, and customer feedback, then a solution that can integrate with the likes of Hadoop, Spark, and NoSQL repositories is likely appropriate. Be sure to take into account the types of data that run through your business and then match that up with the appropriate provider. 5. Cloud, on-prem, or both? A hybrid approach is a growing trend in the enterprise market as it provides organizations the ability to execute integration in both on-prem and cloud environments. Thus, organizations are able to interchange data to and from either framework as a way to gain business agility, manage cloud delivery, and address the need for data sharing between environments. On-prem data management is certainly not dead, but a hybrid approach will set your organization up nicely for the future, even if cloud exposure is currently limited.
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