Risk areas to apply the data cleansing pattern.
不应该应用数据清理模式的领域。
Value proposition of the data cleansing pattern.
数据清理模式的价值主张。
The development costs depend largely on the complexity of the data cleansing task.
开发成本主要取决于数据清理任务的复杂性。
Data cleansing is an important step both in data warehousing and data mining.
数据清洗是数据仓库和数据挖掘中非常重要的一个环节。
The data cleansing service receives data with an undetermined level of data quality as input.
数据清理服务接受数据质量为未确定的数据作为输入。
As you might imagine, design is the most critical and complex phase in the data cleansing process.
正如您可能想到的，设计是数据清理流程中最重要和最复杂的阶段。
In many cases, the data cleansing pattern is applied together with the data consolidation pattern.
在很多情况下，数据清理模式与数据整合模式一起应用。
An important aspect of the data cleansing pattern is its focus on reusability at an enterprise level.
数据清理模式的重要方面是，其注重企业级的可重用性。
Therefore, the data cleansing server needs to be able to scale in order to process large data volumes.
因此，数据清理服务器需要能够进行扩展，以处理大量数据。
The SOA context for data cleansing allows for standardization and matching of individual request strings.
数据清理的soa上下文允许对各个请求字符串进行标准化和匹配。
Data cleansing - how to decide which names are misspellings or are equivalent but slightly different?
数据清洗-如何决定哪些名字拼写错误或相当，但略有不同的？
The potential revenue benefits and customer experience are realized by deploying data cleansing as a service.
潜在收益和客户体验是通过将数据清理作为服务部署来实现的。
First, data cleansing and repository building are almost always carried out on a project by project basis.
首先，清理数据和构建存储库几乎总是按每个项目逐一进行。
It is fairly common to apply the data cleansing pattern against sets of bulk data as well as individual records.
对大量数据应用数据清理模式与对各个记录应用此模式一样常见。
This makes the migration of underlying data cleansing algorithms (RuleSets) from one dataset to another difficult.
这使得将底层数据清理算法 (RuleSet)从一个数据集迁移到另一个数据集变得很困难。
Product implementations of the data cleansing pattern vary in the range of formats they can support for input data.
数据清理模式的产品实现对输入数据支持的格式有很大变化。
Figure 1 illustrates the high-level architecture of applying the data cleansing pattern in the traditional context.
图1显示了在传统上下文中应用数据清理模式的抽象体系结构。
The traditional context of the data cleansing pattern is the database layer, which is where it is most often applied.
数据清理模式的传统上下文是数据库层，经常将数据清理模式应用到此层。
Many implementations of the data cleansing pattern provide sophisticated tools to develop, test, and deploy the cleansing rules.
很多数据清理模式的实现都提供了成熟的工具来开发、测试和部署清理规则。
When applying the data cleansing pattern, it is important to understand how it impacts the following nonfunctional requirements.
应用数据清理模式时，务必了解其如何影响以下非功能需求。
As described earlier, the data cleansing pattern can turn inconsistent (and hence, useless) data into a valuable strategic asset.
正如前面所述，数据清理模式可能会将不一致的数据(因此会没有用处)返回到宝贵的策略资产。
A computer algorithm for data cleansing, no matter how cleverly constructed, can only address a very small subset of data problems.
无论计算机提供的数据清理算法构造如何巧妙，也只能解决数据问题当中非常小的一部分。
After briefly describing the value of this approach, you'll learn the context in which the data cleansing pattern should be applied.
简单描述了此方法后，我们将了解应用数据清理模式的上下文。
This can be used for fraud detection, which is, together with data cleansing, the second major application of deviation detection.
这可用于检测欺诈，这是偏差检测的第二个主要应用。
They also surface information processing capabilities such as the results of analytical and scoring algorithms, data cleansing rules, etc.
它们还可提供各种信息处理功能，如通过分析和评分算法、数据清理规则等进行处理。
The data cleansing pattern specifies a recommended practice for how to improve the data quality of persistent data either at entry or later.
数据清理模式指定有关如何在输入时或稍后提高持久性数据的数据质量的建议性实践。
The data cleansing activities (parsing or separation of values, standardization, matching and survivorship) are specified as cleansing rules.
数据清理活动(解析或值的分隔、标准化、匹配和生存)被指定为清理规则。
The data consolidation pattern is often combined with the data cleansing pattern so that data-quality issues can be addressed during consolidation.
数据整合模式通常与数据清理模式结合在一起，这样就可以在整合的过程中处理数据质量的问题。
The more complex and varied the transformation requirements, the more sophisticated the run-time transformation or the data cleansing server must be.
转换需求越复杂，变化越多，运行时转换或数据清理服务器一定就越复杂。
The more complex and varied the transformation requirements, the more sophisticated the run-time transformation or the data cleansing server must be.
转换需求越复杂，变化越多，运行时转换或数据清理服务器一定就越复杂。
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