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.
Govern and Evaluate Research Data Quality
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Master market forecasting and trend analysis. Learn to use historical data to predict demand and evaluate the strategic impact of emerging trends.
Details to know
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Recently updated!
February 2026
Taught in English
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Build your subject-matter expertise
This course is part of the Advanced Survey Design & Statistical Analysis Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 2 modules in this course
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.
What's included
2 videos1 reading2 assignments
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.
What's included
2 videos2 readings1 assignment
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