Data Quality
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To be useful and yield proper analytical results, data must be of sufficient quality. As data volume increases, the question of internal consistency within data becomes significant, regardless of fitness for use for any particular external purpose. This lesson investigates the key dimensions of data quality and data quality assurance.
Objectives
Upon completion of this lesson, you will be able to
Upon completion of this lesson, you will be able to
- formulate the issues of data quality
- define quality metrics
Required Readings
Example Code
- TBD
Supporting Software & Tools
- TBD
Suggested Readings
- Cai, L., & Zhu, Y. (2015). The Challenges of Data Quality and Data Quality Assessment in the Big Data Era. Data Science Journal, 14, 2. DOI: http://doi.org/10.5334/dsj-2015-002