Business intelligence (BI) solutions, including data mining, data warehousing and data marts, are exploding in size as they evolve into mission-critical workloads. According to the Palo Alto Management Group, a leading BI consulting firm, the average data warehouse will grow 36 times in size over the next three years. The mainframe has long been famous for its capacity and ability to process large volumes of data with ease. As companies reengineer their businesses around BI solutions, they are increasingly evaluating the value the mainframe can bring to data warehousing. Early data warehouse implementations were often developed on less expensive, dedicated systems that needed to be accessed only eight or ten hours a day. These systems were limited in scope and size, with little impact on day-to-day business should there be an outage.

As BI applications surge into companies' business operations areas, these limitations create intolerable conditions when problems arise, resulting in costly outages. Windows for system and data maintenance are disappearing as companies demand constant access to data to meet global business requirements.

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