Data Redundancy
Data redundancy refers to the duplication of data within a database or data storage system. This can occur when the same piece of data is stored in multiple locations or when multiple copies of the same data are stored in a single location. While some level of redundancy can be useful for data backup and recovery purposes, excessive redundancy can lead to wasted storage space and increased processing time. In data science and artificial intelligence, data redundancy can also lead to inaccuracies in analysis and modeling, as duplicated data can skew results and create biases. Therefore, it is important for data scientists and AI experts to carefully manage and minimize data redundancy in their systems.
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