Essentials of Quantitative Data Management

CT Score

1500

#0 of 0 in SPH BS

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SPH BS723 or consent of instructor This course offers a comprehensive foundation in research data management, emphasizing the intersection between traditional data management practices and emerging data science approaches. Starting with the essentials of data planning and quality management, students will explore the full research data lifecycle, from initial data collection through to data sharing, secure storage, and regulatory compliance. In response to key concerns highlighted in the NIH’s 2018 Strategic Plan for Data Science, such as the need for standardized practices, data interoperability, and a skilled workforce, this course equips students with the practical skills to manage data responsibly and effectively. Core topics include developing a Data Management Plan (DMP) that integrates study protocol requirements, establishing robust quality control processes, and implementing regulatory- compliant procedures. Through hands-on experience, students will learn to design Case Report Forms, create secure electronic data capture systems, use programming for data cleaning, derive variables, and harmonize datasets in line with standards such as CDISC, HL7, and PhenX. Additional focus is given to data privacy, ethical considerations, data governance, and the FAIR principles to ensure that data is handled transparently and responsibly. By the end of the course, students will be prepared to contribute meaningfully to research and clinical data management, ensuring data integrity, reproducibility, and regulatory alignment→SPH BS 751→unlocks 0 courses

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