...理解数据和数据的来源(Understanding) 2、获取相关知识与技术(Acquisition) 3、整合与检查数据(Integration and checking) 4、去除错误或不一致的数据(Data cleaning) 5、建立模型和假设(Modeland hypothesisdevelopment) 6、实际数据挖掘工作(Dat...
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理解资料与进行的工作获取相关知识与技术(Acquisition)融合与查核资料(Integration and checking)去除错误或不一致的资料(Data cleaning)发展模式与假设(Model and hypothesis)实际资料挖掘工作测试与检核所挖掘的资料(Tes...
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Data integration can involve complex transformation rules, error checking and data standardization techniques.
数据集成可以涉及复杂的转换规则,错误检查和数据标准化技术。
In a continuous integration environment, programmers are writing code, running the build and tests on their own workstations, and checking in multiple times a day.
在持续集成的环境中,程序员需要编写代码,在工作站上运行构建和测试,一天内多次进行检入。
If a team waits a long time between checking code in and deploying a build, members of that team frequently spend a significant amount of time addressing build breaks and integration issues.
如果团队在签入代码和部署生成这两项操作之间等待了较长时间,则团队的成员经常需要花大量时间来解决生成中断和集成问题。
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