Explore data quality fundamentals, data stakeholders and tooling, common data quality issues, and the data lifecycle.
Course details
This theoretical course is designed for data professionals, stakeholders at data organizations, data leadership, and professionals interested in data quality. Mark Freeman—a data engineer and tech lead—presents a high-level

Overview

of data quality, a measure of how well data meets a company's expectations for accuracy, completeness, consistency, reliability, and validity. In addition to course content, complete a final project that involves a provided code repository to review and an analytics report with data quality issues. Identify data quality issues and make recommendations on how to fix them. This course equips you with a strong understanding of the concepts underpinning data quality.
Homepage:

https://www.linkedin.com/learning/data-quality-core-concepts

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