Integration and transformation of data primarily aim to achieve what?

The primary aim of integration and transformation of data is to enhance the efficiency and usability of the data, particularly in terms of its organization and structure. This means that space efficiency plays a critical role, as effective data integration helps to reduce redundancy, streamline data storage, and facilitate easier access and processing of data.

By transforming data into a more efficient format or structure, organizations can optimize their databases and minimize wasted space. This ensures that data is stored in a way that conserves resources and lowers costs. When data is properly integrated and transformed, it becomes more manageable and can be processed faster, leading to improved overall performance in data handling.

In contrast, while data analysis, formatting, and recovery are important aspects of data management, they are not the primary goals of integration and transformation. Data analysis refers to examining data for insights, data formatting involves preparing data for specific uses, and data recovery deals with retrieving lost data. Therefore, focusing on space efficiency aligns best with the main objective of data integration and transformation.