Running head: DATA MINING
Data mining is a process of finding out any patterns, anomalies, or correlation within
a large dataset to predict a specific outcome of the venture (Rutkowski, Jaworski, and Duda,
2020). Data mining requires the use of a broad range of techniques to ensure the gathered
information can increase revenues, improve customer relationships, cut costs, and reduces the
risks to be encountered in the process. Data mining was first introduced in the 1990s, where it
was primarily focused on three areas artificial intelligence, statistics, and machine learning
(Rutkowski, Jaworski and Duda, 2020). Data mining technology ensured there was constant
evolution that was witnessed in the industry, and there was the limitless potential of big data
that was explored. It facilitated the affordable computation of power.
Benefits of data mining
Data mining is used to make predictions over the future based on the analysis that has
been conducted over the available data presented (Joseph and Thanakumar, 2019). Thus
company management has the opportunity to make decisions on different unexpected issues
that may crop up, and this enables companies to make better and more informed decisions.
Data mining ensures there is better information optimization that is guaranteed. Thus,
companies can opt to use data mining to ensure they increase their website optimization
(Joseph and Thanakumar, 2019). Marketing teams prefer to use information gathered from
data mining to champion their different marketing strategies that can be put in place for the
company products and services. About the marketing campaigns, the marketers get the
opportunity to categorize the consumer's groups with ease and use their resources to gather
the desired results with ease. Companies make use of data mining to measure on the
profitable factors that are proposed for the company (Joseph and Thanakumar, 2019). Once
the company is aware of the correct measures to undertake on how to meet the consumer's
needs effectively, then the company can increase its brand loyalty (Joseph and Thanakumar,
Data mining techniques
Different techniques have been put in place to ensure data mining is highly effective
(Saa, Al-Emran, and Shaalan, 2019). First, tracking patterns which are one of the most
commonly used techniques that require the analyst to make an observation on the presented
data and establish a model. Second, a classification that is identified as a more complex
technique that involves collection form a wide range...
15 Million Students Helped!
Sign up to view the full answer