Data mining is a statistical tool for extracting information from a large existing database. The information is extracted in the form of data set, subjected to statistical analysis tools, and conclusions are drawn from it. In statistics, data sets are very important in predicting outcomes. Large corporations store information in the form of raw data. This data has no use for the firm unless it is converted into a form that can be understood. Consequently, data mining is very essential in management decision-making. For instance, the data obtained can be used to cut costs, do procurement planning, enhance customer relationship, or to increase revenues.
Data Mining and Artificial Intelligence
Artificial intelligence (AI) is the process of using machines to simulate the human intelligence system. In artificial intelligence, machines are programmed to acquire information, reason out, and to make conclusions. Data mining and artificial intelligence is intertwined through coding programs. When properly programmed and trained, AI can derive meaning from large data sets with minimal human intervention, simplfying the decision-making process.
Data Mining and Machine Learning
Machine learning is a function of the AI systems that enables them to learn automatically and improve on their delivery without having to be re-programmed. Data mining allows the system to access necessary data. The AI then creates a new algorithm and updates from the current algorithm. Hence, it is able to learn a new task. When data mining comes with additional unnecessary information, the additional data is referred to as “noise”. The correlation between data mining, machine learning, and artificial intelligence makes them inseparable tools in data management.