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Thankfully, with widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analyticalprocessing applications such as AI or BI solutions.
Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analyticalprocessing applications such as AI or BI solutions.
Thankfully, with the widespread adoption of cloud computing and the Internet of Things, data has never been more readily available in today’s business world. Cubes are multi-dimensional datasets that are optimized for analyticalprocessing applications such as AI or BI solutions.
Consumption This pillar consists of various consumption channels for enterprise analytical needs. It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers.
Ingestion migration implementation is segmented by tenants and type of ingestion patterns, such as internal database change data capture (CDC); data streaming, clickstream, and Internet of Things (IoT); public dataset capture; partner data transfer; and file ingestion patterns.
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