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"data deployment" is a correct and usable term in written English.
You can use it when referring to the process of loading data from one system to another, such as when loading a new database for use. For example, "We are preparing for the data deployment process to begin tomorrow."
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Case studies of big data deployment in the Chinese financial industry and market are discussed.
Historic shifts in the industry – notably to electric power and autonomous driving – make data deployment and optimal utilization especially important.
"To get started, customers should not jump into an enterprise-wide big data deployment before they really know what data has useful information," Bhambhri says.
A significant benefit of this technique is that the cost of securing a big data deployment is reduced.
The IDG enterprise study, referred to above, reports that many companies are investing in the skill sets necessary for big data deployment, including Data Scientists (27%), Data Architects (24%), Data Analysts (24%), Data Visualizers (23%), Research Analysts (21%), and Business Analysts (21%).
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Zettaset has developed a distribution-agnostic management platform for Apache Hadoop-based big data deployments.
Of course, the cloud isn't ideal for all big data deployments.
But for most big data deployments, the cloud is the best way to go.
And despite changing healthcare data deployments, many organizations remain stubbornly focused on network and endpoint security, says Carlisle.
This is Linux optimised for commercial deployments and, whatever you think of Larry Ellison personally, he probably knows more about commercial data deployments than most.
"While the majority of big data deployments fail due to over complexity, iguazio's platform has proven to be simple, fast and secure, making it exceptional for artificial intelligence and machine learning use cases.
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