KNOWLEDGE DISCOVERY DATABASES (KDD) PROCESS IN DATA MINING

Ljupco Markuseski, LjM and Zdravkoski Igor, IZ and Andonovski Miroslav, MA and Jovanoska Aleksandra, AJ (2019) KNOWLEDGE DISCOVERY DATABASES (KDD) PROCESS IN DATA MINING. INTERNATIONAL CONFERENCE PROCEEDING. pp. 529-539. ISSN 978-9989-695-65-0

Warning
There is a more recent version of this item available.
[thumbnail of Paper Ljupce Markusheski PhD.docx] Text
Paper Ljupce Markusheski PhD.docx

Download (285kB)

Abstract

Data Mining is a powerful tool for companies to extract the most important information from their data warehouse. These tools allow you to predict future trends and behaviors in order to be able to provide activities based on specific knowledge. Volume of information is increasing every day that we can handle from business transactions, scientific data, sensor data, Pictures, videos, etc. So, we need a system that will be capable of extracting essence of information available and that can automatically generate report, views or summary of data for better decision-making.
Data mining is used in business to make better managerial decisions by:
 Automatic summarization of data,
 Extracting essence of information stored,
 Discovering patterns in raw data.
Data Mining also known as Knowledge Discovery in Databases, refers to the nontrivial extraction of implicit, previously unknown and potentially useful information from data stored in databases.
Keywords: Data Minig, tools, databases, data warehouse, knowledge.

Item Type: Article
Subjects: Scientific Fields (Frascati) > Social Sciences > Economics and Business
Divisions: Faculty of Economics
Depositing User: Mr Dimitar Risteski
Date Deposited: 23 Dec 2019 09:10
Last Modified: 23 Dec 2019 09:10
URI: https://eprints.uklo.edu.mk/id/eprint/2265

Available Versions of this Item

Actions (login required)

View Item View Item