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Data, Data Everywhere. Technology: The data deluge. EIGHTEEN months ago, Li & Fung, a firm that manages supply chains for retailers, saw 100 gigabytes of information flow through its network each day. Now the amount has increased tenfold. During 2009, American drone aircraft flying over Iraq and Afghanistan sent back around 24 years' worth of video footage. New models being deployed this year will produce ten times as many data streams as their predecessors, and those in 2011 will produce 30 times as many. Everywhere you look, the quantity of information in the world is soaring. According to one estimate, mankind created 150 exabytes (billion gigabytes) of data in 2005. Plucking the diamond from the waste A few industries have led the way in their ability to gather and exploit data. Mobile-phone operators, meanwhile, analyse subscribers' calling patterns to determine, for example, whether most of their frequent contacts are on a rival network.
There's much further to go. Now for the bad news But the data deluge also poses risks. The Merits of Controlled Redundancy. The Merits of Controlled Redundancy One of the principles underlying a true database is that there is no duplication of data: viz, there is no redundancy. Thus, the conceptual data model is pure; and yet for other equally valid reasons of ruggedness and reliability, there is a strong case for designed and inbuilt controlled redundancy. Another valid reason is operational efficiency. After having examined, reported on and recovered 250000 orphaned transactions in a failed database back in ’97, we had a serious rethink of the purity of no redundancy. Since then we have adopted an approach with limited controlled redundancy of which the following comprises 2 examples, each incorporated for a different reason.
Generally, it has also been the accepted view that the conceptual data model is kept pure and thus, any redundancy is left to be introduced in the Schema. Example 2: Duplication of data in 2 different places in 2 different ways. Call to Action: Deal With Data Growth.