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KNOWLEDGE DISCOVERY AND DATA MANAGEMENT USING GENERIC ALGORITHMS
(Sri Ramakrishna College of Arts and Science for Women, 2019-01) T, Saranya; D, Nivetha
The term Knowledge Discovery in Databases, or KDD for short, refers to the broad process of finding knowledge in data, and emphasizes the "high-level" application of particular data mining methods. It is of interest to researchers in machine learning pattern recognition, databases, statistics,artificial intelligence, knowledge acquisition for expert systems, and data visualization. The unifying goal of the KDD process is to extract knowledge from data in the context of large databases. It does this by using data mining methods (algorithms) to extract (identify) what is deemed knowledge, according to the specifications of measures and thresholds, using a database along with any required pre-processing, sub sampling, and transformations of that database.
BIG DATA
(Sri Sankara Arts and Science College, 2018) T, Saranya; D, Nivetha
Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency. And it has one or more of the following characteristics – high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media - much of it generated in real time and in a very large scale.