关于此 专项课程

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This specialization aims to explore the Total Data Quality framework in depth and provide learners with more information about the detailed evaluation of total data quality that needs to happen prior to data analysis. The goal is for learners to incorporate evaluations of data quality into their process as a critical component for all projects. We sincerely hope to disseminate knowledge about total data quality to all learners, such as data scientists and quantitative analysts, who have not had sufficient training in the initial steps of the data science process that focus on data collection and evaluation of data quality. We feel that extensive knowledge of data science techniques and statistical analysis procedures will not help a quantitative research study if the data collected/gathered are not of sufficiently high quality. This specialization will focus on the essential first steps in any type of scientific investigation using data: either generating or gathering data, understanding where the data come from, evaluating the quality of the data, and taking steps to maximize the quality of the data prior to performing any kind of statistical analysis or applying data science techniques to answer research questions. Given this focus, there will be little material on the analysis of data, which is covered in myriad existing Coursera specializations. The primary focus of this specialization will be on understanding and maximizing data quality prior to analysis.
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初级
完成课程大约需要 3 个月
建议进度:3 小时/周
英语(English)
可分享的证书
完成后获得证书
100% 在线课程
立即开始,按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
初级
完成课程大约需要 3 个月
建议进度:3 小时/周
英语(English)

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此专项课程包含 3 门课程

课程1

课程 1

The Total Data Quality Framework

课程2

课程 2

Measuring Total Data Quality

课程3

课程 3

Design Strategies for Maximizing Total Data Quality

提供方

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密歇根大学

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