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Data Cleansing
Data cleansing or data cleaning is the process of detecting and correcting (or removing) corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate or irrelevant parts of the data and then replacing, modifying, or deleting the dirty or coarse data. Data cleansing may be performed interactively with data wrangling tools, or as batch processing through scripting 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 of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Storage Record
In computer science{{citation needed, date=July 2016, a storage record is: * A group of related data, words, or fields treated as a meaningful unit; for instance, a Name, Address, and Telephone Number can be a "Personal Record". * A self-contained collection of information about a single object; a record is made up of a number of distinct items, called fields. * In IBM mainframes, a ''record'' is a basic unit of device-to-program data transfers. Mainframe files, properly called data sets, are traditionally structured collections of records, as opposed to modern byte stream access files. Records may have a fixed length or variable length. In Unix-like systems, a number of programs (for example, awk, join, and sort) are designed to process data consisting of records (called lines) each separated by newlines, where each record may contain a number of fields separated by spaces, commas, or some other character. See also * Block (data storage) * Object composition * Record (computer s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Investment
Investment is the dedication of money to purchase of an asset to attain an increase in value over a period of time. Investment requires a sacrifice of some present asset, such as time, money, or effort. In finance, the purpose of investing is to generate a return from the invested asset. The return may consist of a gain (profit) or a loss realized from the sale of a property or an investment, unrealized capital appreciation (or depreciation), or investment income such as dividends, interest, or rental income, or a combination of capital gain and income. The return may also include currency gains or losses due to changes in the foreign currency exchange rates. Investors generally expect higher returns from riskier investments. When a low-risk investment is made, the return is also generally low. Similarly, high risk comes with a chance of high losses. Investors, particularly novices, are often advised to diversify their portfolio. Diversification has the statistical effec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grammars
In linguistics, the grammar of a natural language is its set of structural constraints on speakers' or writers' composition of clauses, phrases, and words. The term can also refer to the study of such constraints, a field that includes domains such as phonology, morphology, and syntax, often complemented by phonetics, semantics, and pragmatics. There are currently two different approaches to the study of grammar: traditional grammar and theoretical grammar. Fluent speakers of a language variety or ''lect'' have effectively internalized these constraints, the vast majority of which – at least in the case of one's native language(s) – are acquired not by conscious study or instruction but by hearing other speakers. Much of this internalization occurs during early childhood; learning a language later in life usually involves more explicit instruction. In this view, grammar is understood as the cognitive information underlying a specific instance of language production. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, 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, data governance is used to form agreed upon definitions and standards for data quality. In such cases, data cleansing, including standardization, may be required in order to ensure data quality. Definitions Defining data quality is difficult due to the ma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Morgan Kaufmann
Morgan Kaufmann Publishers is a Burlington, Massachusetts (San Francisco, California until 2008) based publisher specializing in computer science and engineering content. Since 1984, Morgan Kaufmann has published content on information technology, computer architecture, data management, computer networking, computer systems, human computer interaction, computer graphics, multimedia information and systems, artificial intelligence, computer security, and software engineering. Morgan Kaufmann's audience includes the research and development communities, information technology (IS/IT) managers, and students in professional degree programs. The company was founded in 1984 by publishers Michael B. Morgan and William Kaufmann and computer scientist Nils Nilsson. It was held privately until 1998, when it was acquired by Harcourt General and became an imprint of the Academic Press, a subsidiary of Harcourt. Harcourt was acquired by Reed Elsevier in 2001; Morgan Kaufmann is now an imprint ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical
Statistics (from German: ''Statistik'', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An experim ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Referential Integrity
Referential integrity is a property of data stating that all its references are valid. In the context of relational databases, it requires that if a value of one attribute (column) of a relation (table) references a value of another attribute (either in the same or a different relation), then the referenced value must exist. For referential integrity to hold in a relational database, any column in a base table that is declared a foreign key can only contain either null values or values from a parent table's primary key or a candidate key. In other words, when a foreign key value is used it must reference a valid, existing primary key in the parent table. For instance, deleting a record that contains a value referred to by a foreign key in another table would break referential integrity. Some relational database management systems (RDBMS) can enforce referential integrity, normally either by deleting the foreign key rows as well to maintain integrity, or by returning an error and n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Integrity
Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire Information Lifecycle Management, life-cycle and 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. 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 not to be confus ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Units Of Measurement
A unit of measurement is a definite magnitude (mathematics), magnitude of a quantity, defined and adopted by convention or by law, that is used as a standard for measurement of the same kind of quantity. Any other quantity of that kind can be expressed as a multiple of the unit of measurement. For example, a length is a physical quantity. The metre (symbol m) is a unit of length that represents a definite predetermined length. For instance, when referencing "10 metres" (or 10 m), what is actually meant is 10 times the definite predetermined length called "metre". The definition, agreement, and practical use of units of measurement have played a crucial role in human endeavour from early ages up to the present. A multitude of System of measurement, systems of units used to be very common. Now there is a global standard, the International System of Units (SI), the modern form of the metric system. In trade, weights and measures is often a subject of governmental r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Consistency
In classical deductive logic, a consistent theory is one that does not lead to a logical contradiction. The lack of contradiction can be defined in either semantic or syntactic terms. The semantic definition states that a theory is consistent if it has a model, i.e., there exists an interpretation under which all formulas in the theory are true. This is the sense used in traditional Aristotelian logic, although in contemporary mathematical logic the term ''satisfiable'' is used instead. The syntactic definition states a theory T is consistent if there is no formula \varphi such that both \varphi and its negation \lnot\varphi are elements of the set of consequences of T. Let A be a set of closed sentences (informally "axioms") and \langle A\rangle the set of closed sentences provable from A under some (specified, possibly implicitly) formal deductive system. The set of axioms A is consistent when \varphi, \lnot \varphi \in \langle A \rangle for no formula \varphi. If there e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Accuracy And Precision
Accuracy and precision are two measures of ''observational error''. ''Accuracy'' is how close a given set of measurements ( observations or readings) are to their ''true value'', while ''precision'' is how close the measurements are to each other. In other words, ''precision'' is a description of '' random errors'', a measure of statistical variability. ''Accuracy'' has two definitions: # More commonly, it is a description of only '' systematic errors'', a measure of statistical bias of a given measure of central tendency; low accuracy causes a difference between a result and a true value; ISO calls this ''trueness''. # Alternatively, ISO defines accuracy as describing a combination of both types of observational error (random and systematic), so high accuracy requires both high precision and high trueness. In the first, more common definition of "accuracy" above, the concept is independent of "precision", so a particular set of data can be said to be accurate, precise, both, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Foreign Key
A foreign key is a set of attributes in a table that refers to the primary key of another table. The foreign key links these two tables. Another way to put it: In the context of relational databases, a foreign key is a set of attributes subject to a certain kind of inclusion dependency constraints, specifically a constraint that the tuples consisting of the foreign key attributes in one relation, R, must also exist in some other (not necessarily distinct) relation, S, and furthermore that those attributes must also be a candidate key in S. In simpler words, a foreign key is a set of attributes that ''references'' a candidate key. For example, a table called TEAM may have an attribute, MEMBER_NAME, which is a foreign key referencing a candidate key, PERSON_NAME, in the PERSON table. Since MEMBER_NAME is a foreign key, any value existing as the name of a member in TEAM must also exist as a person's name in the PERSON table; in other words, every member of a TEAM is also a PERSON. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
