:: In most organizations, corporate information is their most valuable asset, the key ingredient with which innovative new business models are built. Companies are leveraging Enterprise Data Warehouse to streamline infrastructure, improve Business Intelligence (BI) and save money.

:: IT executives are being pressured to better manage information assets; companies need an overarching plan to prioritize business information based on its strategic value. Many companies are turning to enterprise wide data management as a solution.

:: Data mining and Data Management as an analytic discipline is neither as obvious as query and reporting nor as carefully positioned, marketing wise, as online analytic processing (OLAP). It encompasses several disparate techniques and is not tightly linked to any particular business domain or function.

:: Unlike OLAP's slice-and-dice style of analyzing data cubes, which isn't hard to grasp or master, data mining has long been enveloped in an aura of abstruse, academic inaccessibility. Overall, data mining means and delivers different things to different people. Whatever it means, it can be a daunting undertaking.

:: Nonetheless, based on its successes and promise, data mining has become a must-have element of enterprise analytic tools. There remain many obstacles, however, to broad inclusion of data mining in everyday, operational business intelligence (BI).