Govern and Evaluate Research Data Quality

本课程是 Advanced Survey Design & Statistical Analysis 专项课程的一部分

位教师：LearningMate

访问权限由 Coursera Learning Team 提供

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master market forecasting and trend analysis. Learn to use historical data to predict demand and evaluate the strategic impact of emerging trends.

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

3 任务¹

AI 评分请参见免责声明

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Advanced Survey Design & Statistical Analysis 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有2个模块

This course builds data governance and quality management capabilities for research professionals. Learners will develop skills in applying metadata tagging for effective data governance and evaluating data quality against defined standards. Through practical application, learners will build the technical capabilities needed to implement robust data management practices that ensure information integrity and accessibility.

This module introduces the core principles of data governance and the critical role of metadata. Learners will explore why consistent data tagging is essential for preventing costly errors, using real-world examples as a guide. They will learn how to interpret governance policies to determine and apply correct metadata, transforming raw data into reliable, governed assets.

涵盖的内容

2个视频1篇阅读材料2个作业

In this module, learners shift from establishing governance to maintaining it. They will learn how to monitor data quality by evaluating Key Performance Indicators (KPIs) against organizational standards. Using a case study based on the UK Government's COVID-19 data error, learners will practice identifying quality failures and creating formal issue tickets to drive the remediation process, ensuring data remains trustworthy over time.