International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 7 124 - 127 ______________________________________________________________________________________ 124 IJRITCC | July 2018, Available @ http://www.ijritcc.org _______________________________________________________________________________________ Data Mining Concepts A survey paper Parul Mahawar Dept. of Computer Science Arya college of Engineering and IT, RTU Jaipur, Rajasthan parul.18m@gmail.com Vishal Shrivastava Professor, Dept. of Computer Science Arya College of Engineering and IT, RTU Jaipur, Rajasthan Vishal500371@yahoo.co.in Abstract—Data Mining is a significant field in today’s data-driven world. Understanding and implementing its concepts can lead to discovery of useful insights. This paper discusses the main concepts of data mining, focusing on two main concepts namely Association Rule Mining and Time Series Analysis Keywords- Data Mining, Association Rule Mining, Time Series Analysis __________________________________________________*****_________________________________________________ I. DATA MINING A. The idea behind Data Mining The world is constantly experiencing an exponential data growth. Sensor data, social media streams , images, video and mobile data have contributed a lot to this massive increase. However, all this contributes to unstructured data. Proper mining of this unstructured data is important because insights, patterns and concepts are deep buried in this human language communication data. Good Mechanisms are needed to locate, extract, organize and store this data. Here is whereData mining comes into play. Various definitions of Data Mining have been proposed like ―The efficient discovery of previously unknown pattern in large databases‖ [1] or ―the non-trivial extraction of implicit, previously unknown and potentially useful information from data in database‖ [2]. Data Mining is thus a process to extract useful information from large amount of data. This data can be stored in database, data warehouse or any other information repository. It is also referred as knowledge mining from database, data analysis, data archaeology and knowledge extraction. B. Data Mining System Architecture There are various steps involved in extracting knowledge from large data sets.All these steps form the data mining system architecture and are explained below as: - • Data sources- Data warehouse,databases,text files and world wide web are the key data sources. This data as coming from multiple sources so is in different formats. The necessary data is cleaned, integrated and passed to the server. • Database or Data Warehouse Server- It contains the processed data from various data sources. The job of this server is to retrieve the relevant data based on data mining request of the user • Data Mining Engine- It is the core component of Data Mining System It contains modules which perform mining task like clustering, classification, prediction and time series analysis. • Pattern Evaluation Modules- Here the interestingness of patterns is measured with the help of a threshold value. • Graphical User Interface– It acts as a communication link between user and Data Mining system.When a user specifies a query, this module interacts with the system and displays the result in user- friendly format. • Knowledge Base- This module mainly benefits the Pattern Evaluation Module and Data Mining Engine. Pattern Evaluation interacts with the knowledge base to get inputs and update the existing ones if required. Search engine also use the knowledge base for getting more accurate and reliable results. Figure 1- Data Mining System Architecture