Author: Mr. Dayakar Babu Kancherla

Publisher: Xoffencerpublication

Published: 2024-05-15

Total Pages: 198

ISBN-13: 8197370885

Data mining is a topic that is currently trending in the research world and has captured the attention of a wide variety of sectors in our everyday lives. As a result of the enormous amount of data, there is an imminent requirement to transform big data into information and data that can be used. Controlling production, conducting scientific research, designing engineering projects, managing businesses, and conducting market research are all examples of the knowledge that may be gained from using applications. The process of data mining is thought to have emerged as a consequence of the proliferation of datasets and the development of information technologies. In the process of designing following techniques, the evolutionary routes that have been seen in database industries are taken into consideration. These techniques include the development of datasets, the collection of data, and the supervision of databases for the purpose of data storage and retrieval in order to achieve effective data analysis for improved understanding. Beginning in the year 1960, the information technologies and databases have undergone a methodical evolution, transitioning from simple and traditional processing models to more complex and prevalent database models. Since 1970, the analysis and design of database models have accompanied the invention of relational databases, data organizing methods, indexing, and data modeling tools. This has contributed to the development of these tools. Additionally, the consumers were able to obtain instantaneous access to the data through the utilization of user interfaces, query processing, and query languages. To put it another way, data mining is a method that is utilized for the purpose of extracting knowledge from large databases. Taking into consideration a variety of fields, such as information retrieval, databases, machine learning, and statistics, has led to the development of the products and functionalities that are currently used in data mining. When it comes to the Knowledge Discovery in Databases (KDDs) process, other areas of computer science have encountered a significant problem that is associated with graphics and multimedia systems. Knowledge discovery and discovery (KDD) is a term that refers to the total process of gaining meaningful knowledge from data. KDD is designed to demonstrate the results of the KDD process in a substantial manner.