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Data Classification (business Intelligence)
In business intelligence, data classification has close ties to data clustering, but where data clustering is ''descriptive'', data classification is ''predictive''. In essence data classification consists of using variables with known values to predict the unknown or future values of other variables. It can be used in e.g. direct marketing, insurance fraud detection or medical diagnosis.Kimball, R. et al. (2008). ''The Data Warehouse Lifecycle Toolkit. (2. Ed.)''. Wiley. The first step in doing a data classification is to cluster the data set used for category training, to create the wanted number of categories. An algorithm, called the ''classifier'', is then used on the categories, creating a descriptive model for each. These models can then be used to categorize new items in the created classification system.Golfarelli, M. & Rizzi, S. (2009). ''Data Warehouse Design : Modern Principles and Methodologies.'' McGraw-Hill Osburn. Effectiveness According to Golfarelli and Rizzi, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Business Intelligence
Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data analysis and management of business information. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics. BI tools can handle large amounts of structured and sometimes unstructured data to help identify, develop, and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability, and help them take strategic decisions. Business intelligence can be used by enterprises to support a wide range of business ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Clustering
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis itself is not one specific algorithm, but the general task to be solved. It can be achieved by various algorithms that differ significantly in their understanding of what constitutes a cluster and how to efficiently find them. Popular notions of clusters include groups with small distances between cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Type
In computer science and computer programming, a data type (or simply type) is a set of possible values and a set of allowed operations on it. A data type tells the compiler or interpreter how the programmer intends to use the data. Most programming languages support basic data types of integer numbers (of varying sizes), floating-point numbers (which approximate real numbers), characters and Booleans. A data type constrains the possible values that an expression, such as a variable or a function, might take. This data type defines the operations that can be done on the data, the meaning of the data, and the way values of that type can be stored. Concept A data type is a collection or grouping of data values. Such a grouping may be defined for many reasons: similarity, convenience, or to focus the attention. It is frequently a matter of good organization that aids the understanding of complex definitions. Almost all programming languages explicitly include the notion of da ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Variable (research)
In science and research, an attribute is a quality of an object (person, thing, etc.).Earl R. Babbie, ''The Practice of Social Research'', 12th edition, Wadsworth Publishing, 2009, , p. 14-18 Attributes are closely related to variables. A variable is a logical set of attributes. Variables can "vary" – for example, be high or low. How high, or how low, is determined by the value of the attribute (and in fact, an attribute could be just the word "low" or "high"). ''(For example see: Binary option)'' While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing. In data processing data are often represented by a combination of ''items'' (objects organized in rows), and multiple variables (organized in columns). Values of each variable statistically "vary" (or are distributed) across the variable's domain. A domain is a set of all possible values that a variable is allowed to have. The values are orde ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Direct Marketing
Direct marketing is a form of communicating an offer, where organizations communicate directly to a pre-selected customer and supply a method for a direct response. Among practitioners, it is also known as ''direct response marketing''. By contrast, advertising is of a mass-message nature. Response channels include toll-free telephone numbers, reply cards, reply forms to be sent in an envelope, websites and email addresses. The prevalence of direct marketing and the unwelcome nature of some communications has led to regulations and laws such as the CAN-SPAM Act, requiring that consumers in the United States be allowed to opt-out. Overview Intended targets are selected from larger populations based on vendor-defined criteria, including average income for a particular ZIP code, purchasing history and presence on other lists. The goal is "to sell directly to consumers" without letting others "join (the) parade." Popularity A 2010 study by the Direct Marketing Association ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Insurance Fraud
Insurance fraud is any act committed to defraud an insurance process. It occurs when a claimant attempts to obtain some benefit or advantage they are not entitled to, or when an insurer knowingly denies some benefit that is due. According to the United States Federal Bureau of Investigation, the most common schemes include premium diversion, fee churning, asset diversion, and workers compensation fraud. Perpetrators in the schemes can be insurance company employees or claimants. False insurance claims are insurance claims filed with the fraudulent intention towards an insurance provider. Insurance fraud has existed since the beginning of insurance as a commercial enterprise.Manes, Alfred. "Insurance Crimes." p. 34. [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
