Data Mining in Contemporary Business

Over the past decades, technological development had a significant influence on the business environment. In particular, the latest advances in technology created opportunities for businesses and institutions to collect and analyze large volumes of information, thus giving rise to data mining. According to Joseph (2013), data mining is one of the steps used by organizations to generate knowledge that can be applied to fulfill organizational goals. For example, data mining can be used by governments to enhance security by identifying threats to citizens, as well as by businesses to determine market segments and trends (Joseph, 2013). Hence, data mining is crucial for companies to succeed in today’s business world.

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As mentioned above, one particular application area that makes data mining essential for contemporary businesses is marketing. Based on research, the study of data mining in marketing is mostly related to the concept of big data analytics (BDA). Kudyba (2014) explains that data mining is one of the processes involved in BDA, and thus it enables companies to determine patterns and trends that could affect the popularity of their products or services. I believe that data mining leads to better marketing decisions and helps businesses to succeed in today’s world. This is particularly evident when looking at targeted advertisements, which are based on collecting information about individual customers’ preferences. Targeted advertisements based on high-quality data can be compelling because they are tailored to each person’s needs. Additionally, many companies, including Apple, apply data mining to understand how people use their products and incorporate this knowledge in future products to make them more popular. The many uses of data mining make it vital for businesses willing to achieve a significant market share using effective marketing.


Joseph, M. V. (2013). Significance of data warehousing and data mining in business applications. International Journal of Soft Computing and Engineering, 3(1), 329-333.

Kudyba, S. (Ed.). (2014). Big data, mining, and analytics: Components of strategic decision making. Boca Raton, FL: CRC Press.

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