Data Warehousing and Data Mining

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Data Warehousing and Data mining

December, 9 2013

Data Mining and Data Warehousing

Companies and organizations all over the world are blasting on the scene with data mining and data warehousing trying to keep an extreme competitive leg up on the competition. Always trying to improve the competiveness and the improvement of the business process is a key factor in expanding and strategically maintaining a higher standard for the most cost effective means in any business in today’s market. Every day these facilities store large amounts of data to improve increased revenue, reduction of cost, customer behavior patterns, and the predictions of possible future trends; say for seasonal reasons. Data
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The question still remains whether or not the user purchased, but this was a source of enticement for a customer to potentially what Amazon likes to call impulse buying. This is not something that has been openly admitted, however there are several case studies (Coskun Samli, A. A., Pohlen, T. L., & Bozovic, N. 2002). Not soon after is when Wal-Mart picked up on the trend and placed their destination towards data mining and data warehousing. Now Walmart on its own stores 460 terabytes on Teradata mainframes which is actually is half the total usage of the internet today. Imagine this on top of the physical locations where there are roughly about 100 million patrons entering Walmart’s doors every day. If this does not convince you of the possibilities of data mining I am not sure what else would convince you other wise and with a profit margin to be spread between the shareholders and CEO’s of roughly about 64 billion dollars a year I do believe that I would model after these two giants to make a statement in the business world.
Utilizing different techniques for data mining is extremely important for what may work for ne may not work for the other. With the
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