Data integration challenge You are asked to build a BI report, but required data lives partly in SQL Server and partly in Oracle. This situation is an example of:

Introduction / Context:
BI work often begins with data integration—consolidating information spread across multiple operational systems. When the same subject area lives in separate platforms (e.g., SQL Server and Oracle), analytics teams must reconcile schemas, keys, and semantics before reporting.

Given Data / Assumptions:

• Two RDBMS platforms: SQL Server and Oracle.
• Overlapping business entities and measures exist across them.
• Goal: unify data for a single report.

Concept / Approach:

This is a textbook case of non-integrated data. The problem is not necessarily quality (dirty) or encoding conflicts (inconsistent), though those may appear later; the primary challenge is that the data is siloed and must be integrated via ETL/ELT, virtualization, or federation.

Step-by-Step Solution:

Verification / Alternative check:

Data warehousing methodologies emphasize integration as a central step (conformed dimensions, integrated fact tables) precisely because organizations frequently operate multiple OLTP systems.

Why Other Options Are Wrong:

• Dirty/inconsistent: may occur but are secondary here.
• Wrong format: not the core issue—both are relational systems.
• Over-normalized: a modeling concern, not cross-system integration.

Common Pitfalls:

• Attempting to report directly across silos without harmonization, leading to mismatched totals.

Final Answer:

Non-integrated data (data siloed across systems).