What is a likely outcome of effective data enrichment?

Effective data enrichment enhances the quality and usefulness of data by adding relevant context and improving its accuracy. When data is enriched, it becomes more informative, allowing organizations to draw better insights from it. This process might involve merging datasets, adding metadata, or transforming raw data so that it reflects a more complete picture of the information being analyzed.

By improving the accuracy, businesses can make more reliable decisions based on this enriched data, ultimately leading to enhanced business intelligence outcomes. The improved context helps analysts and decision-makers understand not just the 'what' of the data but also the 'why' and 'how,' leading to more informed strategies and actions. This outcome aligns directly with the goals of business intelligence, which aims to leverage data for actionable insights.

Other outcomes, such as increased storage requirements and higher costs of BI tools, may occur in certain contexts of data management but are not the primary benefits of effective data enrichment. Similarly, while reduced data entry tasks could be a byproduct of improved processes, it is not the main objective or outcome of enriching data.