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Data Warehousing and Data Mining

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According to Lee, the most popular definition is a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process (2014). Basically a data warehouse is a copy of transaction data specifically structured for query and analysis. According to Frand, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cut costs, or both (1997). There are many benefits of data warehousing. Yes, it will cost large amounts of money from businesses to have a data warehouse but, in the long run it is worth it to have in a corporation. One benefit is that data warehouses stores and presents information in a way that allows management to make important decisions (Prathap, 2014). Management and even executives can look at the business as a whole instead of by each department. According to Prathap, another benefit of data warehouses is their ability to handle server tasks connected to querying which is not used in most transaction systems (2014). Creating queries and reports can take time and with data warehousing, the server can handle the tasks in a timely fashion. Again, according to Prathap, one of the most important benefits of data warehouses is that they set the stage for an environment where a small amount of technical knowledge about databases can be used to write queries and speed of the maintenance of these queries (2014). Someone who is not very technical in writing queries could use the data warehouse to help with ease and queries can be run on a regular basis. Imagine before data warehouses having to extract multiple data and reports from different systems to gather all the information you could. This would take too much time and...

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