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Definition
| A form of report, often requested by recipients, that tells them some piece of usually time-related information, such as notification of the time for a meeting. |
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Term
| Business intelligence (BI) application server |
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Definition
| A computer programs that delivers BI (business intelligence) application results in a variety of formats to various devices for consumption by BI users. |
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| Business intelligence (BI) |
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Definition
| Information containing patterns, relationships, and trends. |
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| Business intelligence (BI) application |
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Definition
| Software that uses a tool on a particular type of data for a particular purpose. |
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| Business intelligence (BI) system |
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Definition
| An information system, having all five IS components, that provides the right information, to the right user, at the right time. |
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| Business intelligence (BI) tool |
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Definition
| A computer program that implements a particular BI technique. BI tools include reporting tools, data-mining tools, and knowledge-management tools. |
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Definition
| E-commerce data that describes a customer’s clicking behavior. Such data includes everything the customer does at the Web site. |
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Definition
| An unsupervised data-mining technique whereby statistical techniques are used to identify groups of entities that have similar characteristics. A common use for cluster analysis is to find groups of similar customers in data about customer orders and customer demographics. |
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Definition
| In market-basket terminology, the probability estimate that two items will be purchased together. |
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Definition
| The sale of related products; salespeople try to get customers who buy product X to also buy product Y. |
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Definition
| The more attributes there are, the easier it is to build a data model that fits the sample data but that is worthless as a predictor. |
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Definition
| Facilities that prepare, store, and manage data for reporting and data mining for specific business functions. |
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Definition
| The application of statistical techniques to find patterns and relationships among data for classification and prediction. |
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Definition
| Tools that use statistical techniques, many of which are sophisticated and mathematically complex, to process data to look for hidden patterns. |
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Definition
| Facilities that prepare, store, and manage data specifically for reporting and data mining. |
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Definition
| A hierarchical arrangement of criteria for classifying customers, items, and other business objects. |
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Definition
| A characteristic of an OLAP measure. Purchase date, customer type, customer location, and sales region are examples of dimensions. |
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Term
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Definition
| Problematic data. Examples are a value of B for customer gender and a value of 213 for customer age. Other examples are a value of 999–999–9999 for a U.S. phone number, a part color of gren, and an email address of WhyMe@GuessWhoIAM-Hah-Hah.org. All these values are problematic when data mining. |
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Definition
| With an OLAP report, to further divide the data into more detail. |
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Definition
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Term
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Definition
| A message that notifies a system user of an out-of-the-ordinary—exceptional—event. |
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Definition
| Knowledge-sharing system that is created by interviewing experts in a given business domain and codifying the rules used by those experts. |
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Term
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Definition
| The level of detail in data. Customer name and account balance is large-granularity data. Customer name, balance, and the order details and payment history of every customer order is smaller granularity. |
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Term
| If... then . . . decision rules |
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Definition
| Format for rules derived from a decision tree (data mining) or by interviewing a human expert (expert systems). |
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Term
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Definition
| The most important content function of knowledge-management applications, which uses keyword search to determine whether content exists and provides a link to its location. |
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Term
| Knowledge management (KM) |
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Definition
| The process of creating value from intellectual capital and sharing that knowledge with employees, managers, suppliers, customers, and others who need it. |
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Term
| Knowledge-management (KM) tools |
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Definition
| Computer applications used to store employee knowledge and to make that knowledge available to employees, customers, vendors, and others who need it. The source of KM tools is human knowledge, rather than recorded facts and figures. |
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Term
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Definition
| In market-basket terminology, the ratio of confidence to the base probability of buying an item. Lift shows how much the base probability changes when other products are purchased. If the lift is greater than 1, the change is positive; if it is less than 1, the change is negative. |
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Term
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Definition
| A data-mining technique for determining sales patterns. A market-basket analysis shows the products that customers tend to buy together. |
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Definition
| The data item of interest on an OLAP report. It is the item that is to be summed, averaged, or otherwise processed in the OLAP cube. Total sales, average sales, and average cost are examples of measures. |
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Definition
| A popular supervised data-mining technique used to predict values and make classifications, such as “good prospect” or “poor prospect.” |
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Definition
| A presentation of an OLAP measure with associated dimensions. The reason for this term is that some products show these displays using three axes, like a cube in geometry. Same as OLAP report. |
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Definition
| Computer server running software that performs OLAP analyses. An OLAP server reads data from an operational database, performs preliminary calculations, and stores the results of those calculations in an OLAP database. |
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Term
| Online analytical processing (OLAP) |
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Definition
| A dynamic type of reporting system that provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data. Such reports are dynamic because users can change the format of the reports while viewing them. |
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Definition
| Program similar to a Web server, but with a customizable user interface. |
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Definition
| A report that the user must request. To obtain a pull report, a user goes to a Web portal or a business intelligence (BI) Web server and clicks a link or button to cause the reporting system to produce and deliver the report. |
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Definition
| Reports sent to users according to a preset schedule or whenever a particular event occurs. |
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Term
| Real Simple Syndication (RSS) |
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Definition
| A standard for subscribing to content sources; similar to an email system for content. |
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Term
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Definition
| A type of supervised data mining that estimates the values of parameters in a linear equation. Used to determine the relative influence of variables on an outcome and also to predict future values of that outcome. |
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Definition
| A special case of a business intelligence (BI) application server that serves only reports. |
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Term
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Definition
| A type of business intelligence tool, these programs read data from a variety of sources, process that data, format the data into structured reports, and delivery those reports to the users who need them. |
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Definition
| A way of analyzing and ranking customers according to the recency, frequency, and monetary value of their purchases. |
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Definition
| A data source that transmits using an RSS standard. The output of an RSS feed is consumed by an RSS reader. |
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Definition
| A program by which users can subscribe to magazines, blogs, Web sites, and other content sources; the reader will periodically check the sources, and if there has been a change since the last check, it will place a summary of the change and a link to the new content in an inbox. |
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Definition
| Concerns the unintended release of protected information through the release of a combination of reports or documents that are independently not protected. |
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Definition
| A form of data mining in which data miners develop a model prior to the analysis and apply statistical techniques to data to estimate values of the parameters of the model. |
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Definition
| In market-basket terminology, the probability that two items will be purchased together. |
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Definition
| A form of data mining whereby the analysts do not create a model or hypothesis before running the analysis. Instead, they apply the data-mining technique to the data and observe the results. With this method, analysts create hypotheses after the analysis to explain the patterns found. |
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