What distinguishes data abstraction from data extraction?

Data abstraction involves presenting data in a simplified format, focusing on the essential characteristics and hiding unnecessary details. It allows users to interact with data at a higher conceptual level, enhancing understanding and usability. In contrast, data extraction refers to the process of retrieving data from multiple sources or databases for further analysis or processing. Data extraction involves identifying relevant datasets, transforming them into a suitable format, and loading them into a target destination for storage or analysis. While data abstraction emphasizes clarity and simplicity in data representation, data extraction focuses on retrieving raw data efficiently from diverse sources for specific purposes, such as business intelligence or reporting.