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Data Quality
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for tsintended uses in operations, decision making and planning". Data is deemed of high quality if it correctly represents the real-world construct to which it refers. Apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose. People's views on data quality can often be in disagreement, even when discussing the same set of data used for the same purpose. When this is the case, businesses may adopt recognised international standards for data quality (See #International Standards for Data Quality below). Data governance can also be used to form agreed upon definitions and standards, including international standards, for data quality. In such cases, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Data Cleansing
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. Data cleansing can be performed interactively using data wrangling tools, or through batch processing often via scripts or a data quality firewall. After cleansing, a data set should be consistent with other similar data sets in the system. The inconsistencies detected or removed may have been originally caused by user entry errors, by corruption in transmission or storage, or by different data dictionary definitions of similar entities in different stores. Data cleaning differs from data validation in that validation almost invariably means data is rejected from the system at entry and is performed at the time of entry, rather than on batches of data. The actual process ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Qualitative Data
Qualitative properties are properties that are observed and can generally not be measured with a numerical result, unlike Quantitative property, quantitative properties, which have numerical characteristics. Description Qualitative properties are properties that are observed and can generally not be measured with a numerical result. They are contrasted to Quantitative property, quantitative properties which have numerical characteristics. Evaluation Although measuring something in qualitative terms is difficult, most people can (and will) make a judgement about a behaviour on the basis of how they feel treated. This indicates that qualitative properties are closely related to emotional impressions. A test method can result in qualitative data about something. This can be a categorical result or a binary classification (e.g., pass/fail, go/no go, Conformity, conform/non-conform). It can sometimes be an engineering judgement. Categorization The data that all share a qualitat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Computer Data Storage
Computer data storage or digital data storage is a technology consisting of computer components and Data storage, recording media that are used to retain digital data. It is a core function and fundamental component of computers. The central processing unit (CPU) of a computer is what manipulates data by performing computations. In practice, almost all computers use a storage hierarchy, which puts fast but expensive and small storage options close to the CPU and slower but less expensive and larger options further away. Generally, the fast technologies are referred to as "memory", while slower persistent technologies are referred to as "storage". Even the first computer designs, Charles Babbage's Analytical Engine and Percy Ludgate's Analytical Machine, clearly distinguished between processing and memory (Babbage stored numbers as rotations of gears, while Ludgate stored numbers as displacements of rods in shuttles). This distinction was extended in the Von Neumann archite ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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List Of System Quality Attributes
Within systems engineering, quality attributes are realized non-functional requirements used to evaluate the performance of a system. These are sometimes named architecture characteristics, or "ilities" after the suffix many of the words share. They are usually architecturally significant requirements that require architects' attention. In software architecture, these attributed are known as "architectural characteristic" or non-functional requirements. Note that it's software architects' responsibility to match these attributes with business requirements and user requirements. Note that synchronous communication between software architectural components, entangles them and they must share the same architectural characteristics. Quality attributes Notable quality attributes include: * accessibility * accountability * accuracy * adaptability * administrability * affordability * agility * auditability * autonomy * availability * compatibility * composability * con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Information Systems
An information system (IS) is a formal, sociotechnical, organizational system designed to collect, process, store, and distribute information. From a sociotechnical perspective, information systems comprise four components: task, people, structure (or roles), and technology. Information systems can be defined as an integration of components for collection, storage and processing of data, comprising digital products that process data to facilitate decision making and the data being used to provide information and contribute to knowledge. A computer information system is a system, which consists of people and computers that process or interpret information. The term is also sometimes used to simply refer to a computer system with software installed. "Information systems" is also an academic field of study about systems with a specific reference to information and the complementary networks of computer hardware and software that people and organizations use to collect, filter, p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Ontological
Ontology is the philosophical study of being. It is traditionally understood as the subdiscipline of metaphysics focused on the most general features of reality. As one of the most fundamental concepts, being encompasses all of reality and every entity within it. To articulate the basic structure of being, ontology examines the commonalities among all things and investigates their classification into basic types, such as the categories of particulars and universals. Particulars are unique, non-repeatable entities, such as the person Socrates, whereas universals are general, repeatable entities, like the color ''green''. Another distinction exists between concrete objects existing in space and time, such as a tree, and abstract objects existing outside space and time, like the number 7. Systems of categories aim to provide a comprehensive inventory of reality by employing categories such as substance, property, relation, state of affairs, and event. Ontologists disagree re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Semiotics
Semiotics ( ) is the systematic study of sign processes and the communication of meaning. In semiotics, a sign is defined as anything that communicates intentional and unintentional meaning or feelings to the sign's interpreter. Semiosis is any activity, conduct, or process that involves signs. Signs often are communicated by verbal language, but also by gestures, or by other forms of language, e.g. artistic ones (music, painting, sculpture, etc.). Contemporary semiotics is a branch of science that generally studies meaning-making (whether communicated or not) and various types of knowledge. Unlike linguistics, semiotics also studies non-linguistic sign systems. Semiotics includes the study of indication, designation, likeness, analogy, allegory, metonymy, metaphor, symbolism, signification, and communication. Semiotics is frequently seen as having important anthropological and sociological dimensions. Some semioticians regard every cultural phenomenon as being able to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Customer Service
Customer service is the assistance and advice provided by a company to those who buy or use its products or services, either in person or remotely. Customer service is often practiced in a way that reflects the strategies and values of a firm, and levels vary according to the industry. Good quality customer service is usually measured through customer retention. Successful customer service interactions are dependent on employees "who can adjust themselves to the personality of the customer". Customer service for some firms is part of the firm's intangible assets and can differentiate it from others in the industry. One good customer service experience can change the entire perception a customer holds towards the organization. It is expected that AI-based chatbots will significantly impact customer service and call centre roles and will increase productivity substantially. Many organisations have already adopted AI chatbots to improve their customer service experience.Krishnan, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Data Integrity
Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire Information Lifecycle Management, life-cycle. It is a critical aspect to the design, implementation, and usage of any system that stores, processes, or retrieves data. The term is broad in scope and may have widely different meanings depending on the specific context even under the same general umbrella of computing. It is at times used as a proxy term for data quality, while data validation is a prerequisite for data integrity. Definition Data integrity is the opposite of data corruption. The overall intent of any data integrity technique is the same: ensure data is recorded exactly as intended (such as a database correctly rejecting mutually exclusive possibilities). Moreover, upon later Data retrieval, retrieval, ensure the data is the same as when it was originally recorded. In short, data integrity aims to prevent unintentional changes to information. Data integrity is no ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Outlier
In statistics, an outlier is a data point that differs significantly from other observations. An outlier may be due to a variability in the measurement, an indication of novel data, or it may be the result of experimental error; the latter are sometimes excluded from the data set. An outlier can be an indication of exciting possibility, but can also cause serious problems in statistical analyses. Outliers can occur by chance in any distribution, but they can indicate novel behaviour or structures in the data-set, measurement error, or that the population has a heavy-tailed distribution. In the case of measurement error, one wishes to discard them or use statistics that are robust statistics, robust to outliers, while in the case of heavy-tailed distributions, they indicate that the distribution has high skewness and that one should be very cautious in using tools or intuitions that assume a normal distribution. A frequent cause of outliers is a mixture of two distributions, wh ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Cross Tabulation
In statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the multivariate frequency distribution of the variables. They are heavily used in survey research, business intelligence, engineering, and scientific research. They provide a basic picture of the interrelation between two variables and can help find interactions between them. The term ''contingency table'' was first used by Karl Pearson in "On the Theory of Contingency and Its Relation to Association and Normal Correlation", part of the '' Drapers' Company Research Memoirs Biometric Series I'' published in 1904. A crucial problem of multivariate statistics is finding the (direct-)dependence structure underlying the variables contained in high-dimensional contingency tables. If some of the conditional independences are revealed, then even the storage of the data can be done in a smarter way (see Lauritzen (2002)). In order to do this one can use in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Bounds Checking
In computer programming, bounds checking is any method of detecting whether a variable is within some bounds before it is used. It is usually used to ensure that a number fits into a given type (range checking), or that a variable being used as an array index is within the bounds of the array (index checking). A failed bounds check usually results in the generation of some sort of exception signal. As performing bounds checking during each use can be time-consuming, it is not always done. Bounds-checking elimination is a compiler optimization technique that eliminates unneeded bounds checking. Range checking A range check is a check to make sure a number is within a certain range; for example, to ensure that a value about to be assigned to a 16-bit integer is within the capacity of a 16-bit integer (i.e. checking against wrap-around). This is not quite the same as type checking. Other range checks may be more restrictive; for example, a variable to hold the number of a calen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |