When Honda introduced the Civic in America in 1972, industry experts declared Honda would never succeed because automobiles were too complex and required skills and technology beyond those of the mere motorcycle company. Fast forward to today when Honda’s Civics and Accords are two of North America's top-selling cars.

What changed?

Honda developed the skills and technology to build nimble automobiles, while competitors stayed mired in old paradigms – big cars, poor mileage, and mediocre quality.

This story is being retold today with virtual data marts.

Virtual Data Marts – Solutions with Promise
When data marts and data warehouses were introduced in the mid-1990s, both physical and virtual versions were developed. Proponents valued virtual marts because of their promise of faster time-to-solution and greater agility to better meet fast-changing business requirements. However, critics argued against the virtual approach, contending physical replication and data consolidation were necessary steps prior to executing business intelligence (BI) reporting and analytics.

Technology vendors attempting to develop the first generation of virtual data mart technology lived up to critics’ predictions: they were unable to overcome the complexity in the source data, the fears of bogging down transactions systems, and the need to restructure data from tabular to dimensional form before reporting. As a result, the extract, transform and load (ETL) tool became the de facto solution for the complex data integration requirements of BI.