驱动轮驱动轴的数据变化。
事件处理通常涉及应用程序的数据变化。
Event processing usually involves changing application data.
当数据变化的时候。
我这一代的女性非常可惜，没能改变高管职位的数据变化。
My generation really, sadly, is not going to change the Numbers at the top.
如果你现在需要一个新的通信机制或者数据模式变化了呢？
What if you now need a new communication mechanism or change to a data schema?
这使应用程序能够在数据的存储方式发生变化时继续正常工作。
This enables applications to continue to work despite any change in how data is stored.
随时间变化的数据的一个好例子就是代码列表。
A good example of data that changes over time is code lists.
业务环境是在快速变化的，而业务数据的类型也是如此。
The business climate is changing rapidly, and so are the types of business data.
尤其是最后一次收集后数据发生巨大变化，会造成这种问题。
This is particularly true if the data has changed dramatically since the last statistics collection.
目前尚未数据显示气候变化会对疾病的传播产生何种影响。
Little data currently exists on how diseases will spread in response to climate change.
这样的勘察工作使公司的地图数据跟得上现实的变化。
Such detective work keeps the company’s mapping database up to date.
然而即使这些数据相对发生在他们国内的变化而言，有所保留。
Yet even these figures understate the change that is taking place.
数据层中也一定存在变化点。
工资研究公司ADP同样将在周三发布他们对于私营业工作岗位变化的研究数据。
Payroll company ADP also releases its data on private jobs growth Wednesday.
对数据的再分析显现不出与此前结论的变化。
这种需求变化的一个方面是需要让数据更容易取得。
One aspect of this changing need is for the data to be more available.
这一变化将允许数据库级别上的颗粒度，而不是实例级别上的颗粒度。
This change will allow granularity at the database level, rather than at the instance level.
这里有些技术上的原因，与来自各国的数据不断变化有关。
There were technical reasons for this, with changing data from different countries.
不过其他数据均有变化。
当然，细节部分会因存储数据方式的限制而变化。
Of course, details will vary since how you store your data might be restricted.
这两种数据都需要使用不会频繁变化的数据结构。
如何检测是否在时间序列数据的变化不再明显？
How to detect if change in time series data is no longer significant?
赛车自那以后做了很多变化，比较那些数据会很有趣的。
The car has changed since then, but it will be interesting to compare the data.
探讨如何运用GRACE数据进行重力变化的计算和分析。
It is introduced how to use GRACE data to compute the gravity changes.
面对市场的变化，及时控制、掌握产品及其过程数据显得越来越重要。
Increasingly, immediate access to product and process data is vital for responding to market changes.
数据仓库中的数据不是一成不变的，而是随时间不断变化的。
异常、变化和突发是三类最典型的数据流事件。
Outlier, change and burst are three typical types of events.
美联储也已一改多年惯例，不再向外界公布M3的变化数据。
The Federal Reserve has even stopped publishing M3, a broad measure of the money supply.
美联储也已一改多年惯例，不再向外界公布M3的变化数据。
The Federal Reserve has even stopped publishing M3, a broad measure of the money supply.
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