During data enrichment, how is raw data improved?

Data enrichment is the process of enhancing raw data by integrating it with additional information, typically from various external data sources. This external data can provide context, add new attributes, or help in validating the information, ultimately resulting in a more comprehensive and meaningful dataset.

In this context, combining raw data with external data sources allows for a deeper analysis, and insights that would not be possible with the raw data alone. For instance, if you have customer data, enriching it with demographic information or geographic data from external sources can lead to better customer segmentation, more personalized marketing strategies, and improved decision-making.

While other choices present aspects that could be relevant in data management or manipulation, they do not specifically focus on the idea of enhancement through additional context or new attributes as data enrichment does. Therefore, the process of combining raw data with external data sources stands out as the accurate representation of how raw data is improved during data enrichment.