Abstract Data Warehouse (DW) is widely used in industries over decades to perform the analysis on data to expedite decision-making process. However, the traditional DW is slower in execution due to the huge time overhead of pre-processing stages of Extraction-Transformation-Loading (ETL). On the other hand, often the situations arise where the decision-making are required in real time. Data virtualization is one of the robust approaches over traditional data warehouse that avoids the costly steps of ETL processing. Virtual Data Warehouse (VDW) allows specific analysis for quick decision making even on the unprocessed data. Moreover, VDW could be used by the organizations that maintain DW to take some immediate business decisions for some abrupt changes. This research work performs business trend specific analysis based on VDW to generate business intelligence even in the catastrophic situations. Experimental results reveal, the proposed methodology based on VDW is around thousand times faster than traditional warehouses.

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