Implementing a business intelligence (BI) tool requires integrating data from multiple enterprise applications, and the greatest challenge is often ensuring that data definitions and mappings are consistent and accurate. The CGEIT Review Manual 8th Edition notes that data integration, particularly defining and mapping data sources, is a critical hurdle in BI projects due to varying data formats, structures, and semantics across systems.

Extract from CGEIT Review Manual 8th Edition (Domain 5: Benefits Realization):"The success of business intelligence initiatives depends heavily on the quality and consistency of data. Data definition and mapping from disparate enterprise applications is often the greatest challenge, as inconsistencies in data formats, structures, and meanings can lead to inaccurate insights and project delays." (Approximate reference: Domain 5, Section on Data Management for BI)

Data definition and mapping sources from applications (option D) is the greatest challenge because it involves resolving differences in how data is structured, labeled, and interpreted across systems, which is foundational to BI success.

Why not the other options?

A. Interface issues between enterprise and BI applications: Interface issues are technical but typically less challenging than data mapping, as they can often be addressed with middleware or APIs.

B. The need for staff to be trained on the new BI tool: Training is a manageable challenge that occurs post-implementation and is not as critical as data integration.

C. Large volumes of data fed from enterprise applications: While large data volumes pose a challenge, modern BI tools are designed to handle big data, making data mapping the more significant issue.