• Kajal Khanna
• Ruchi Patira

KDD is termed as Knowledge discovery in databases and it is used to autonomously explore and analyse large data sources. Knowledge discovery in databases is a systematic process for identifying real, valuable, novel, and understandable patterns in complex and large data sets. The core of this process is data mining, which involves inferring algorithms to examine the data, create and discover previously undetected patterns. Analysis, predicting, and understanding of events are accomplished by applying the theory to the evidence. Knowledge discovery and data mining are highly important and essential because of the accessibility and amount of data available nowadays. It is not surprising that both academics and practitioners have access to a range of methodologies given the field's quick growth. There is no method that is always better than another. Data covers performance evaluation approaches and techniques, exemplifies the use of the various methods with examples from real-world applications and software tools, and aims to compile a comprehensive list of all pertinent techniques created in the subject.

KDD, Knowledge Discovery in Database, Data Mining, Data Repositories.

"Knowledge Discovery in Database and Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 10, page no.h205-h209, October-2023, Available :http://www.jetir.org/papers/JETIR2310624.pdf

"Knowledge Discovery in Database and Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 10, page no. pph205-h209, October-2023, Available at : http://www.jetir.org/papers/JETIR2310624.pdf