DLP approaches deal with data in motion, data at rest, and data in use, which are described in Table 2.
DLP方法能处理传输中的数据、闲置数据、使用的数据,如表2所述。
Real-time feeds can be processed efficiently while the data is still in motion, running on scale-out clusters with fail-over capability, and all performed on commodity machines.
具有故障转移功能的可伸缩集群在数据仍然在运动的同时仍然能够高效地处理实时反馈,并且都在商业机器上完成。
Data "in motion" analytics is the analysis of data before it has come to rest on a hard drive or other storage medium.
运动数据分析是指将数据储存在硬盘或其他储存媒介之前对其进行分析。
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