Data mining: foundation and applications

This process helps large organizations to focus on the critical information in their warehouses while. It also helps in predicting the behavioral patterns that assist business firms in making knowledge-driven decisions. This technique can be easily implemented on the existing resources to enhance their value and analyze massive databases to answer future related queries.

Foundation:

This technique came into being as the result of various attempts aimed at simplifying the management of business data stored on computers and comprehensive databases. Enabling organizations to sort big data as per various aspects, data mining improved the way information was handled by organizations and allowed the users to manage and process data with exemplary seamlessness.

Widely used in business communities, data mining is supported by:

* Massive data collection

* Data mining algorithms

* Powerful multiprocessor computers

If industry observers are to be believed, this technique was developed about a decade ago; however, wasn’t being implemented as a mature and reliable tool since it was still in what can be considered as the “preliminary stages”, and hence, could not be considered a reliable alternative solution holding the capacity to outperform older statistical methods being used for data management.

However, after extensive research and development, it was the finally established that this technique, when coupled with high performance datable engines, can make a notable enhancement to the efficacies of big data warehouses.

Applications:

Many companies are leveraging on this technique as it helps them in managing large databases and build a better customer relationship while enhancing their internal processes. Some of the successful applications of data management include:

* A credit card company can adopt this technique to track the transactions of its customers and identify the customers likely to be interested in new credit product. Using a small test mail, the company can discover customers with a notable affinity for the product.

* A large manufacturer of consumer goods can use this technique to enhance its overall revenue. Collecting data from competitor activity and consumer panels can help them in deciding the reason for switching over to another brand or store. This can further help them in planning promotional strategies that assist them in reaching their target audience.

In addition to the aforementioned, data mining is used in various other industries with telecommunication, software development, health care and bio informatics to name a few.

Andy Robert - About Author:
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