What is Data Mining?

Data mining is a method of analyzing large streams of data and using patterns to make predictions. Companies use data mining to gain a competitive edge by maximizing sales revenue, increasing market share, and reducing costs through improved customer satisfaction. A company that has done well in this area can use the data mining technique to analyze their existing products, service, and customers to create new business opportunities and products.

In this article, we will learn about some key techniques like unsupervised machine learning, semi-supervised analysis (K-means), artificial neural network, classification algorithms, and clustering algorithms that are commonly used to solve real-world problems. In this blog post, I will share with you my own experience of using data mining for creating solutions. Data mining helps us to understand our business and find better ways to improve it. Data mining techniques have become very popular among professionals because of their ability to transform data. This technology allows companies to get an opportunity for innovation, creativity, and product development. Nowadays, there are many marketing research reports published online that help companies understand how they perform as per competition.

Data mining is a widely popular practice used by companies to interpret and analyze huge volumes of data. It enables organizations to make decisions on consumer behavior and customer satisfaction which has a direct impact on growth and profit. Data mining can be used either alone or together with other analytics to analyze consumers’ behaviors and discover various strategic and tactical aspects, which leads to greater productivity and profitability for businesses. For example, IBM launched a survey titled “Do Your Employees Have Access to Their Full Potential? To Understand Them Better and Find Ways to Increase Productivity at Work” that uses data mining to understand the performance of employees of different companies based on questions posed by external companies and asked by staffs themselves.

Unsupervised Machine Learning, K-Means Clustering, Artificial Neural Network, Classification Algorithm, and Cluster Analysis: Explained

In this blog post, we will learn how to use these powerful techniques in making your businesses more effective and efficient. Let’s take an early first look at why and when data mining is necessary.


Data Mining
Data Mining