What is data mining?
Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases
Data Mining is a field of study within Computer Science. It is part of the process of Knowledge Discovery from Databases (KDD). The aim of data mining is to find novel, interesting and useful patterns from data using algorithms (methods of finding such information) that will do it in a way that is more computationally efficient than previous methods.
Knowledge Discovery and Data Mining has increased in popularity because of the large amount of stored data that came about as computer storage became cheaper. From this, there was a need to understand it, and techniques to convert data into information are being continually developed and improved.
Data mining techniques usually fall into two categories, predictive or descriptive. Predictive data mining uses historical data to infer something about future events. Descriptive data mining aims to find patterns in the data that provide some information about what the data contains.
Data mining can be used for several purposes by different people and organisations. The most notable users of data mining come from commercial, scientific or government backgrounds.
Commercial entities may use the information gathered through data mining techniques to help discover something about their consumers, to help market their products better. Data mining is also used by search engines, such as google to mine web pages for information relating to your specific search query.
Scientific communities may benefit from data mining by using it to find anomalies, clusters or co-locations to name a few. For example, they could discover a relationship between people getting cancer and the location of a chemical plant.
The government could use data mining techniques to uncover patterns in their data. For example, data mining is used to find unusual patterns in the stock market in order to detect insider trading. Data mining is also used to detect scams sent by email. It could also be used to find unusual behaviour to prevent a terrorist attack.
There are many more applications of data mining, which are continually being expanded. The main requirement for performing data mining is suitable data.
mining the data is called data mining. Mining the text is called text mining
CHARECTERISTICS OF DATA MINING CHARECTERISTICS OF DATA MINING
spatial data mining time series data mining text or multimedia data mining www mining systems
Data mining can uncover interesting patterns. Some cookies will upload solely for the purpose of data mining.
Data warehouse is the database on which we apply data mining.
What is data mining? is data mining another hype? Is it a simple transformation of technology developed from databases, statistics, and machine learning? how the evolution of database technology led to data mining. the steps involved in data mining when viewed as a process of knowledge discovery.
Simply, Data mining is the process of analyzing data from several sources and converting it into useful data.
A data warehouse is the pool of information . The major advantage of data warehouse is that we can archive data that is not used in a long time. To extract data from data warehouse data mining is done.
The term data mining is generally known as the process of analyzing data from many different perspectives in order to correctly organize the data. Sometimes data mining is also called knowledge dicovery.
difference between Data Mining and OLAP
Name three benefits to electronic data storage by incorporating a data mining service
In directed data mining, you are trying to predict a particular data point - the sales price of a house given information about other houses for sale in the neighborhood, for example. In undirected data mining, you are trying to create groups of data, or find patterns in existing data - creating the "Soccer Mom" demographic group, for example. In effect, every U.S. census is data mining, as the government looks to gather data about… Read More
data mining is very important because the particular user will be looking for a pattern not for complete data in the database,it is better to read wanted data than unwanted data.........and other advantage by data mining technique is that only required pattern will be drawn from database with in short time.... One of the data mining tool is :SAS tool(statistical analysis system)
mining two different data sets
SAS is statistical software that can be used as a tool for data mining.
types of data reduction
catch important data from data warehouse.
its when the data is being monitored
Data mining is effectively storing and analysing old pieces of data and predicting what's going to happened in future based on trends and patterns in that data.
Some of the advantages in data mining services include Market Data Research. this provides the companies with large amounts of data for research and development.
A business uses data mining in several different ways. One way a company uses data mining is to get better insight into customers so that they can improve their marketing approach.
Data warehousing and data mining are useful in terms of MIS in the sense that they aggregate all the data and keep it together for MIS programming and tests later on.
to have a detailed study of any form of data. like in web its web mining- to study structure of web sites
There are various features of Data Mining. Some of them are as follows :- Data mining discovers hidden information in your data and also will help marketing companies build models based on historical data to predict who will respond to the new marketing campaigns such as direct mail, online marketing campaign…etc. Data mining gives financial institutions information about loan information and credit reporting.Data mining is a powerful tool that can help you find patterns and… Read More
How do digital dashboard and data mining applications differ from transaction processing applications?
Digital dashboard and data mining applications do not generate new data, but instead are used to summarize existing data to provide information to management
data mining Retail data mining is the process used by large retailers to study trends.
Data mining can help you better understand what your customers buy better helping you understand their needs and wants.
Data mining refers to a company soliciting personal information from users. This information can be used for advertising and can be obtained through cookies dropped on a computer.
Data Mining in C++
Web mining - is the application of data mining techniques to discover patterns from the Web. According to analysis targets, web mining can be divided into three different types, which areWeb usage mining, Web content mining and Web structure mining.
Data mining Is popular in business for information to use for marketing purposes. Data mining recognises patterns and relationships in data in order to help make business more efficient and generally better.
Rob Sullivan has written: 'Introduction to data mining for the life sciences' -- subject(s): Life sciences, Data mining, Methodology, Research
Perhaps the data that you are given.
data warehouse A data warehouse is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. data mining The development of computational algorithms for the identification or extraction of… Read More
Data mining just means gathering information. The purpose of data mining is to collect as much information as possible about any particular issue so that analysts can spot trends and predict what is likely to happen next. It is useful for companies because it helps them tailor their goods and services for the market.
Data mining is a computer science which extract patterns in data sets. It can be used to predict which people are most likely to respond to a sales offer or what type of garment is preferred by a certain type of customer.
online analytical processing uses basic operations such as slice and dice drilldown and roll up on historical data in order to provide multidimensional analysis of data data mining uses knowledge discovery to find out hidden patterns and association constructing analytical models and presenting mining results with visualization tools.
M. Ishaq Bhati has written: 'Cluster effects in mining complex data' -- subject(s): Cluster analysis, Econometrics, Data mining
Sequence mining is a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. It is usually presumed that the values are discrete, and thus time series mining is closely related, but usually considered a different activity. Sequence mining is a special case of structured data mining. There are several key traditional computational problems addressed within this field. These include building efficient databases and… Read More