<p>Data piles up quickly in business applications, and compound annual data growth threatens to bury today's application infrastructure. A senior executive at a major bank remarked, "There are only 3 things certain in life: death, taxes, and data growth."</p><p>Businesses accumulate data across a range of categories, including enterprise applications, data warehouses, user data, and in some cases big data repositories like Hadoop and MongoDB. These massive, unstructured data repositories, created by data hoarders like Google and Facebook, provide new opportunities for businesses a hot and visible area for IT investment.</p><p>Enterprise applications (financials, CRM, ERP, and HCM), however, have been a big data problem for decades and are growing bigger all the time. Five years ago, a "big" database might have contained one or more terabytes of data. Today, large businesses often have applications consuming over ten terabytes of data, and these front-end applications have a tendency to snowball into bigger and bigger data management challenges over their lifecycle.</p><p>In order to provide a business-wide view of data, IT often takes data from front-end applications and rolls it into operational data stores, where the data can then be manipulated and rolled into even bigger data warehouses. Operational data stores can store tens of terabytes of data, and large data warehouses can store hundreds of terabytes of data. In order to provide flexible reporting options (for different marketing divisions or campaigns), these large data warehouses might feed a number of smaller downstream data marts.</p><p><a href="http://www.wired.com/insights/2013/03/the-big-data-snowball-effect/">Keep reading...</a></p>