Data mining is an iterative process that involves discovering patterns in large data sets. It includes methods and techniques such as machine learning, statistics, database systems and etc. The two main data mining objectives are to find out patterns and establish trends and relationship in a dataset in order to solve problems.

The general stages of the data mining process are: problem definition, data exploration, data preparation, modeling, evaluation, and deployment. Core terms related to data mining are classification, predictions, association rules, data reduction, data exploration, supervised and unsupervised learning, datasets organization, sampling from datasets, building a model and etc. [1]

Figure 1. The core of data mining process

The core of data mining process is shown in figure 1. Data mining process is the discovery through large data sets of patterns, relationships and insights that guide enterprises measuring and managing where they are and predicting where they will be in the future. Large amount of data and databases can come from various data sources and may be stored in different data warehousess. And, data mining techniques such as machine learning, artificial intelligence (AI) and predictive modeling can be involved. [2]

The data mining process typically involves the following steps:

1. Business understanding: Define the problem and objectives for the data mining project.
2. Data understanding: Collect and explore the data to gain an understanding of its properties and characteristics.
3. Data preparation: Clean, transform, and preprocess the data to make it ready for analysis.
4. Modeling: Apply a variety of techniques and algorithms to the data to extract useful information and insights.
5. Evaluation: Assess the quality and usefulness of the discovered patterns and models.
6. Deployment: Use the discovered patterns and models to solve the business problem and make decisions.[3]

Benefits of Data Mining:

• Data mining technique helps companies to get knowledge-based information.
• Data mining helps organizations to make the profitable adjustments in operation and production.
• The data mining is a cost-effective and efficient solution compared to other statistical data applications.
• Data mining helps with the decision-making process.
• Facilitates automated prediction of trends and behaviors as well as automated discovery of hidden patterns.
• It can be implemented in new systems as well as existing platforms.
• It is the speedy process which makes it easy for the users to analyze huge amount of data in less time.[4]

Overall, data mining is a crucial step in the data science process, as it helps to identify important patterns and insights that can be used to make informed decisions and drive business value.

Reference:

1. https://www.intellspot.com/data-science-topics/
2. https://barnraisersllc.com/2018/10/01/data-mining-process-essential-steps/
3. https://www.geeksforgeeks.org/data-mining-process/
4. https://www.guru99.com/data-mining-tutorial.html

Cite this article:

Gokula Nandhini K (2023), The core of data mining process, Anatechmaz, pp.68