Data mining means the information we store is known as data and the data that is stored from the other sources known as mining. Mining means mainly known as digging. Here mining means digging the information in the form of data. The main aim of the data mining is examining the large databases in order to generate new information.
Data mining is a process of sorting large data into data sets to identify patterns and establish relationships to solve problems trough data analysis. Here the data coding that you choose is different from the typical values in your databases. Here the large set of data is divided into small pars and the data is set into patterns so that we can get the information easily from the data bases. The typical data addressed here by the data mining. It also involves in many aspects like
Databases and data management aspects,
Post processing of discovered structures
Visualization and online updating
this data mining is in fact because the goal is the extraction of patterns and knowledge from large amounts of data, not the mining of data itself and is frequently applied to any form of large-scale data or any information processing like collection, extraction, statistics, analysis and warehousing.
Data mining tools and techniques:
Data mining techniques are used in many research areas, including mathematics, cybernetics, genetics and marketing. While data mining techniques are a means to drive efficiencies and predict customer behavior, if used correctly, a business can set itself apart from its competition through the use of predictive analysis.
Web mining, a type of data mining used in customer relationship management, integrates information gathered by traditional data mining methods and techniques over the web. Web mining aims to understand customer behavior and to evaluate how effective a particular website is.
Other data mining techniques include network approaches based on multitask learning for classifying patterns, ensuring parallel and scalable execution of data mining algorithms, the mining of large databases, the handling of relational and complex data types, and machine learning. Machine learning is a type of data mining tool that designs specific algorithms from which to learn and predict.
Benefits of data mining:
In general, the benefits of data mining come from the ability to uncover hidden patterns and relationships in data that can be used to make predictions that impact businesses.
Specific data mining benefits vary depending on the goal and the industry. Sales and marketing departments can mine customer data to improve lead conversion rates or to create one-to-one marketing campaigns. Data mining information on historical sales patterns and customer behaviors can be used to build prediction models for future sales, new products and services.
Companies in the financial industry use data mining tools to build risk models and detect fraud. The manufacturing industry uses data mining tools to improve product safety, identify quality issues, manage the supply chain and improve operations