Data mining

Data Mining and Privacy-an ethical look I. Introduction In 2001, the MIT Technology Review listed data mining as one of the top 10 technologies that will change the world.[i] So, what is data mining? For many people, the simple answer is that data mining is the collecting of people’s information when logged onto the Internet. But Webopedia emphasizes that data mining is not the collection of data itself, but the statistical interpretation of it – allowing people to obtain new information

Preparing a data set for analysis in data mining is a more time consuming task. For preparing a data set it requires more complex SQL quires, joining tables and aggregating columns. Existing SQL aggregations have some limitations to prepare data sets because they return one column per aggregated group. In general, significant manual efforts are required to build data sets, where a horizontal layout is required. Also many data mining applications deal with privacy for many sensitive data. Therefore

information regarding data mining and knowledge discovery 4 2.2 Impact of the technology on the use of information at Di Stefano cafe 6 2.3 Impact of the technology on the managers 6 2.4 Business strategy implications associated with the technology 7 2.5 Data mining simplified model for knowledge discovery based on OLAP analysis 8 3.0 Conclusions and recommendations 15 Executive summary This report focuses on the various advantages associated with the adoption and implementation of data warehousing and

ABSTRACT Data mining has popular technology for extracting interesting information for multimedia data sets, such as audio, video, images, graphics, speech, text and combination of several types of data set. Multimedia data are unstructured data or semi-structured data. These data are stored in multimedia database, multimedia mining which is used to find information from large multimedia database system, using multimedia techniques and powerful tools. The current approaches and techniques are explained

to the copious amount of data we have access to today. This large amount of data can be overwhelming. While it once seemed impossible to sort through and extract meaningful patterns from these enormous amounts of data, automated data processing techniques have significantly advanced.

Baker, 2009) (wiley, 2015) Text mining is generally identical to content examination it is the way toward getting brilliant data from text. Fantastic data is ordinarily determined through the concocting of examples and patterns through means, for example, factual example learning. Content mining as a rule includes the way toward organizing the information message typically parsing, alongside the expansion of some

Abstract Data Mining is the non-trivial extraction of potentially useful information about data. In other words, Data Mining extracts the knowledge or interesting information from large set of structured data that are from different sources. There are various research domains in data mining specifically text mining, web mining, image mining, sequence mining, process mining, graph mining, etc. Data mining applications are used in a range of areas such as it is used for financial data analysis, retail

Data Mining DM Defined Is the analysis of (often large) observational data sets to find unsuspected relationships and to summarize the data in novel ways that are both understandable and useful to the data owner Process of analyzing data from different perspectives and summarizing it into useful information A class of database applications that look for hidden patterns in a group of data that can be used to predict future behavior. DM Defined The relationships and summaries derived

Survey on Distributed data mining Dr.S.kannan, Vairaprakash Gurusamy, Associate Professor, Research Scholar, Department of Computer Applications, Department of Computer Applications, Madurai Kamaraj University, Madurai Kamaraj University, skannanmku@gmail.com vairaprakashmca@gmail.com Abstract Traditionally Data Mining is a process of extracting useful knowledge

amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, a repository of data gathered from various sources, including corporate databases, summarized information from internal systems, and data from external sources. Analysis of the data includes simple query and reporting, statistical analysis, more complex multidimensional analysis, and data mining. Data analysis and data mining are a subset