Data mining and warehousing technologies use data about past events to inform better decision-making in the future. Do you believe this stifles innovative thinking, causing companies to become too constrained by the data they are already collecting to think about unexplored opportunities? Compare and contrast both viewpoints in your answer.
There are both positive and negative reviews from companies toward the data mining technology. Positive reviews side is the benefits and usefulness of data mining to their business performance, the prediction from the database that holds past information are quite accurate and it’s important for company to refer before making any future decision. While negative reviews stating that company that use data mining will tend to follow exactly with the future trends and patterns predicted by system, it will cause company unable to think out of the box and thus distort their innovative with the unexplored opportunities.
Data mining technology can generate new business opportunities by two systems known as “Automated prediction of trends and behaviors” and “Automated discovery of previously unknown patterns”.
Automated prediction of trends and behaviors mean data mining automates the process of finding predictive information in a large database. Questions that traditionally required extensive hands-on analysis can now be directly answered from the data. A typical example of a predictive problem is targeted marketing. Data mining uses data on past promotional mailings to identify the targets most likely to maximize return on investment in future mailings. Other predictive problems include forecasting bankruptcy and other forms of default, and identifying segments of a population likely to respond similarly to given events.
While automated discovery of previously unknown patterns are tools that sweep through databases and identify previously hidden patterns. An example of pattern discovery is the analysis of retail sales...
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