Data Mining
Data mining (DM for short) is an interdisciplinary branch of computer science. It is a computational process that uses the intersection of artificial intelligence, machine learning, statistics, and databases to discover patterns in relatively large data sets.It is a computer-assisted technique used for analysis to process and explore large data sets. With the help of data mining tools and methods, organizations can discover hidden patterns and relationships in their data. Data mining transforms raw data into useful knowledge. Companies can use this knowledge to solve problems, analyze the future impact of business decisions, and improve profit margins.The goal of data mining is not to extract or mine data itself, but to extract meaningful or valuable knowledge from a large amount of data.
Types of Data Mining
Data mining can have different branches or specializations depending on the data and the purpose of mining. Following are some examples of data mining.
Process Mining
Process mining is a branch of data mining that aims to discover, monitor and improve business processes. It extracts knowledge from event logs available in information systems and helps organizations understand what happens every day in these processes.
For example, an e-commerce business has many processes such as purchasing, selling, paying, collecting, and shipping. By mining the purchasing data logs, they may find that their supplier delivery reliability is 54%, or that there are suppliers with 12% who always deliver ahead of schedule. They can use this information to optimize their relationships with suppliers.
Text Mining
Text mining or text data mining uses data mining software to read and understand text. Data scientists use text mining to automatically discover knowledge in written resources such as websites, books, emails, reviews, and articles.
For example, a digital media company can use text mining to automatically read comments on its online videos and classify viewer comments as positive or negative.
Predictive Mining
Predictive data mining uses business intelligence to predict trends. It helps business leaders study the impact of their decisions on the company's future and make effective choices.
For example, a company might look at past product return data to design warranty plans that don’t result in losses. Using predictive mining, they would forecast the potential number of returns over the next year and create a one-year warranty plan that takes losses into account when determining product prices.
References
【1】https://zh.wikipedia.org/wiki/%E6%95%B0%E6%8D%AE%E6%8C%96%E6%8E%98