它是甲骨文的点云数据。
We actually have more consumers in our data cloud than they have in theirs.
我们实际上有更多的消费者，在我们点云数据比他们拥有的他们。
The Cloud. We save our data to it, create documents in it, collaborate in it.
我们在云中存储数据，创建文档，并在云中实现协作。
Third, data stored in the cloud may not be safe.
第三，储存在云系统中的数据可能并不安全。
The information cloud abstracts the client from the data.
信息云把客户端从数据抽象出来。
The data are employed in combination with cloud maps.
这些资料与云图结合一起使用。
The data was supported by model simulations of cloud formation.
这些测量数据依托于云体形成的模拟模型。
I am so happy to see voice and data converging and moving into the cloud.
我很高兴看到语音和数据合二为一，并转到了云计算下。
IBM operates a cloud data center for its customers.
IBM为其客户运作一个云数据中心。
As cloud services expand, the same will be true for other documents and data.
随着云服务的扩展，其他文件和资料也会得到这种保护。
Who accesses your data in the cloud is not the only thing to worry about.
“谁访问云中的数据”并不是要担心的惟一问题。
The other key thing is the way data is persisted on the Cloud.
另一个关键是数据在云上的持久化。
Cloud-enabled financial market data solution: For a hybrid cloud.
应用云计算的金融市场数据解决方案：用于混合云。
Another issue is the potential for problems with data in the cloud.
另一个是云中数据潜在的问题。
Typically, data grids would be deployed on top of a cloud.
通常将数据网格部署在云上。
Information cloud: Abstracts access from clients to data.
信息云：把客户端到数据的访问抽象出来。
Synchronization with cloud based data.
对基于云的数据实现同步。
And Puppet is another open source package designed for data center infrastructure (a cloud).
Puppet是另外一种开源包，为数据中心基础设施(一个云)量身设计。
Does the cloud back up your data?
云服务是否备份你的数据？
What if that device contains sensitive data just downloaded from the cloud?
如果该设备包含刚从云端下载的敏感数据怎么办？
Even if your data is "in the cloud," it's still housed somewhere.
即使你的数据已经“在云端”了，但是它仍然是静居于某处的。
A typical example for it is the cloud-enabled financial market data solution.
其典型例子就是应用云计算的金融市场数据解决方案。
Application data backup API - allows backing up application data to the cloud.
应用数据备份api——可以将应用数据备份到云中。
We cloud technology to their own data to calculate.
我们通过云技术对自己的数据进行计算。
The discrete point cloud data sampling from the striation figure is common.
采样于线状图形的离散点云数据也是常见的。
In order to prepare the data for the cloud, the data processor.
为了为云准备数据，数据处理器会。
In the cloud, the data is already backed up.
使用the cloud，数据已经自动备份了。
Read the LIDAR point cloud data, and can be displayed.
读取LIDAR的点云数据，并且可以显示出来。
The problem of data security impedes the spread and application of cloud computing.
云计算自身的数据安全问题阻碍其推广应用。
Cloud detection is absolutely necessary in the processing of satellite remote sensing data.
云检测是卫星遥感数据处理中不可缺少的工作。
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