data mining

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data mining

[′dad·ə ‚mīn·iŋ or dād·ə ‚mīn·iŋ]
(computer science)
The identification or extraction of relationships and patterns from data using computational algorithms to reduce, model, understand, or analyze data.
The automated process of turning raw data into useful information by which intelligent computer systems sift and sort through data, with little or no help from humans, to look for patterns or to predict trends.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.

Data mining

The development of computational algorithms for the identification or extraction of structure from data. This is done in order to help reduce, model, understand, or analyze the data. Tasks supported by data mining include prediction, segmentation, dependency modeling, summarization, and change and deviation detection. Database systems have brought digital data capture and storage to the mainstream of data processing, leading to the creation of large data warehouses. These are databases whose primary purpose is to gain access to data for analysis and decision support. Traditional manual data analysis and exploration requires highly trained data analysts and is ineffective for high dimensionality (large numbers of variables) and massive data sets. See Database management system

A data set can be viewed abstractly as a set of records, each consisting of values for a set of dimensions (variables). While data records may exist physically in a database system in a schema that spans many tables, the logical view is of concern here. Databases with many dimensions pose fundamental problems that transcend query execution and optimization. A fundamental problem is query formulation: How is it possible to provide data access when a user cannot specify the target set exactly, as is required by a conventional database query language such as SQL (Structured Query Language)? Decision support queries are difficult to state. For example, which records are likely to represent fraud in credit card, banking, or telecommunications transactions? Which records are most similar to records in table A but dissimilar to those in table B? How many clusters (segments) are in a database and how are they characterized? Data mining techniques allow for computer-driven exploration of the data, hence admitting a more abstract model of interaction than SQL permits.

Data mining techniques are fundamentally data reduction and visualization techniques. As the number of dimensions grows, the number of possible combinations of choices for dimensionality reduction explodes. For an analyst exploring models, it is infeasible to go through the various ways of projecting the dimensions or selecting the right subsamples (reduction along columns and rows). Data mining is based on machine-based exploration of many of the possibilities before a selected reduced set is presented to the analyst for feedback.

McGraw-Hill Concise Encyclopedia of Engineering. © 2002 by The McGraw-Hill Companies, Inc.

data mining

Analysis of data in a database using tools which look for trends or anomalies without knowledge of the meaning of the data. Data mining was invented by IBM who hold some related patents.

Data mining may well be done on a data warehouse.

ShowCase STRATEGY is an example of a data mining tool.
This article is provided by FOLDOC - Free Online Dictionary of Computing (

data mining

Exploring and analyzing detailed business transactions. It implies "digging through tons of data" to uncover patterns and relationships contained within the business activity and history. Data mining can be done manually by slicing and dicing the data until a pattern becomes obvious. Or, it can be done with programs that analyze the data automatically. Data mining has become an important part of customer relationship management (CRM). In order to better understand customer behavior and preferences, businesses use data mining to wade through the huge amounts of information gathered via the Web. See data miner, Web mining, text mining, OLAP, decision support system, EIS, data warehouse and slice and dice.

Doing It Automatically
This BusinessMiner analysis determined that the most influential factor common to non-profitable customers was their credit limit. (Image courtesy of SAP.)
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References in periodicals archive ?
Usually, the data miner must pool the data into a single usable data repository and then build the necessary data-mining databases from scratch or prepare the data from existing business databases.
Model building is typically a computer-intensive activity that requires both an understanding of the business problem and the data-mining methodology for building the model.
Law enforcement agencies can use data-mining technology to help them deploy their resources, including personnel, more effectively and proactively.
Data-mining technology represents a powerful, user-friendly, and accessible new tool that agencies can use to help them in facing this challenge as they seek to fulfill their missions--ultimately, to ensure the safety and welfare of the public.
But the report indicates just how contentious the data-mining issue is, with two members issuing separate statements outlining their specific disagreements.
Mint are employing data-mining techniques to boost the security of computer networks.
In response to the GAO report, the Center for Democracy and Technology and the Heritage Foundation released a report offering guidelines for developing and using data-mining technologies in ways that would preserve privacy.
"We're talking about data-mining systems that credit-card companies in particular use," McKnight told the Monitor.
* The data-mining systems under testing and development for TIA are not merely "off the sheff" commercial programs; they are far more powerful.
"Although we had much value from it over the years, we are really seeing tremendous value now that we are getting into the [customer relationship management] space, e-business and analytics around using the data with data-mining tools," Sibigtroth said.
The company is relying on data warehousing and data-mining techniques to assist in this effort, Hoffman said.
The federal government's Total Information Awareness (TIA) project, spearheaded by the Defense Advanced Research Projects Agency (DARPA), has been called "the mother of all data-mining projects" by some.