<h2 class="wp-block-heading">What is Cloud Data Management?</h2>



Cloud data management is a model that helps you administer and organize data across cloud storage platforms, either instead of or in combination with on-premises tools. More importantly, it simplifies the communication of an organization’s data across both the cloud and physical storage, as well as between private and public clouds. 



Much like on-premise data management tools, cloud data management tools are often used for disaster recovery, backups, and long-term data filing. Unlike traditional services, however, data management platforms deliver greater flexibility than their physical counterparts due to their lightweight and online nature.&nbsp; 



Cloud data management offers easier scalability than on-premise alternatives as the resources you purchase are virtual, requiring little expense and setup time. Additionally, this on-demand model of data management means companies can usually tailor the services they need exactly to their specifications for <a href="https://www.sisense.com/glossary/cloud-analytics/">cloud analytics</a> and business intelligence. 



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Although cloud management provides new challenges in terms of data architecture and security, it has become an increasingly popular alternative to outright purchasing or even leasing hardware for storage. Instead, companies can sign up for a subscription that has limited overheads and more manageable scalability requirements. 



<h2 class="wp-block-heading">How Can I Use Cloud Data Management?</h2>



Today, most organizations use some hybrid of on-premise and cloud management, but more and more are going full cloud. One of the most common uses for cloud data management services is in administering the processing, warehousing, and access needs of <a href="https://www.sisense.com/product/cloud-bi/">cloud BI</a> tools and other big data analytics suites. 



In these cases, cloud management is used to centralize disparate data streams and sources, communicate directly with the data warehouse system, and let users access data on demand. Moreover, they’re increasingly used for predictive analytics tools that require faster access to data. This is true in both large and small organizations for which data volumes may differ but demands do not. 



Additionally, cloud data management has also become a vital component of the Internet of Things (IoT). Using thousands of connected devices relaying real-time data could quickly become problematic for on-premise services, which would require significant hardware purchases and overall costs for scaling. 



On the other hand, cloud management offers a flexible and easily accessible infrastructure that allows IoT devices to communicate more quickly and efficiently. Importantly, it does not pose the same challenges in terms of scaling and expanding data needs that on-premise tools encounter. 



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Cloud Data Management

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