Fields of Data Mining Application

The science of data mining is a modern science and the main nerve of Business Intelligence Science, and this science has imposed itself strongly in the era of Informatics and technology through its integration with the means of artificial intelligence where the process of data mining provides companies and institutions to explore the most important information in the huge data blocks.

Data mining aims at rapid exploratory analysis of qualitative data and interactive data visualization to increase revenue, optimize spending, target new customers and provide the best customer service.

The concept of data mining:
It is the process that analyzes large-scale sets of data to search for possible relationships, summarizes data in new forms to be understandable and useful to the user, and predicts future behavior to find a logical relationship that summarizes this data in a good and understandable way for the owner.

Data mining techniques are a step towards exploring knowledge in databases, and focus on building future sales forecasts as many variables are taken into studies such as multiple market variables, customer capabilities based on buying habits, and exploring behavior and trends allowing the right decisions to be made at the right time.

The great success of data mining is due to the great growth of data, especially those in data bases and stores, and to competition in the market. An important factor in the success of data mining is to know what is the nature of this data in a way that helps the designer to use algorithms or tools used for specific issues with high accuracy.

Tools for data mining:
In order to do data mining, there are tools to help you such as:
* Summary
* Classification
* Prediction
* Retail
* Correlation analysis
* Detection of changes or deviations

What are the data mining process steps?
• Understanding the nature of business
• Data understanding (data collection, characterization, indicative analysis and Data Quality Achievement)
• Data preparation
• Formulation of solution models
• Evaluation and interpretation of model results
• Publication and distribution of the model

Areas of data mining application:
• Marketing
• Retail
• Banks
• Insurance
• Communications
• Operations management
• Education and Human Development
• The medicine and Medical Sciences
• Space science and astronomy
• Genetic engineering