Costs

In Data Science, costs refer to the expenses incurred in the process of collecting, storing, processing, and analyzing data. These costs can be direct, such as the cost of purchasing hardware and software, or indirect, such as the cost of hiring and training personnel. In addition, costs can also be associated with the quality of data, as poor quality data can lead to additional costs in terms of time and resources required to clean and preprocess the data. Therefore, it is important for organizations to carefully consider the costs associated with data science projects and to develop strategies for managing these costs effectively.

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Data Normalization: Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves breaking down a table into smaller tables and defining relationships between them. The main goal of data normali ... Read More >>
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Costs

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