What outcome does achieving data integration typically aim to facilitate in an organization?

Achieving data integration fundamentally aims to create a cohesive framework where disparate datasets can be understood uniformly across an organization. By establishing a common schema, organizations can ensure that different departments or systems interpret data in the same way, which enhances collaboration and data sharing. This commonality is crucial for making informed decisions based on unified data insights, leading to greater efficiency and accuracy in analysis.

While easier data entry processes and reduced costs of data analysis are desirable outcomes that may result from improved data management, they are not the primary aim of data integration. Data integration is more concerned with enabling consistent and comprehensive views of data rather than merely simplifying individual tasks. Increased redundancy of data sources is typically counterproductive to the goals of data integration, as it can lead to confusion and inefficiencies rather than clarity and streamlined operations. Thus, the establishment of a common schema stands out as the key outcome of successful data integration.