Apply data quality metrics to data from identified data stores to ascertain data quality levels.
将数据质量度量指标应用到来自已识别的数据存储的数据上，以确定数据质量级别。
The scorecard keeps evolving, and users give their input on which data quality metrics they need most.
计分卡不断演变，用户输入他们最需要的数据质量标准。
A very common type of data produced by testing, one which is often a source for quality metrics, is defects.
测试产生的一个非常普通的数据类型是缺陷，它通常是质量度量方法的来源。
The effects of this obstacle on test management are constantly changing priorities and shifting tasks, as well as reduced data for test results and quality metrics.
在测试管理中这种障碍的影响是不断变换优先级，不断转换工作以及为测试结果和质量检测方法简化数据。
Data quality components with all their associated metadata (rules and rule sets, metrics, bindings, execution history, folder associations, etc.)
数据质量组件及其所有相关元数据(规则和规则集、指标、绑定、执行历史、文件夹关联，等等)。
Data quality components with all their associated metadata (rules and rule sets, metrics, bindings, execution history, folder associations, etc.)
数据质量组件及其所有相关元数据(规则和规则集、指标、绑定、执行历史、文件夹关联，等等)。
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