granularization
Granularization is a process used in data management and data mining to transform data from a coarse-grained level to a fine-grained level. This process involves breaking down larger data units into smaller, more detailed components. The primary goal of granularization is to enhance the granularity of data, making it more precise and detailed, which can be beneficial for various analytical tasks.
There are several methods for granularization, including:
1. Data Aggregation: This involves combining multiple data points into a single, more detailed unit. For example,
2. Data Decomposition: This method breaks down complex data structures into simpler, more granular components. For
3. Data Transformation: This involves converting data from one format to another to increase its granularity.
Granularization is particularly useful in scenarios where detailed insights are required, such as in market research,
However, it is important to note that increasing the granularity of data can also lead to challenges