The term "data mining" was used in a similarly critical way by economist Michael Lovell in an article published in the Review of Economic Studies in 1983. In the 1960s, statisticians and economists used terms like data fishing or data dredging to refer to what they considered the bad practice of analyzing data without an apriori hypothesis. Data mining is also known as Knowledge Discovery in Data (KDD). For segmenting the data and evaluating the probability of future events, data mining uses sophisticated mathematical algorithms. Data mining involves effective data collection and warehousing as well as computer processing. This helps businesses be closer to their objective and make better decisions. As an application of data mining, businesses can learn more about their customers and develop more effective strategies related to various business functions and in turn leverage resources in a more optimal and insightful manner. Data mining has applications in multiple fields, like science and research. It implies analyzing data patterns in large batches of data using one or more software. In simple words, data mining is defined as a process used to extract usable data from a larger set of raw data. Data mining depends on effective data collection, warehousing, and computer processing. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs. Data mining is a process used by companies to turn raw data into useful information.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |