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Data Profiling
Data profiling is the process of examining the data available from an existing information source (e.g. a database or a file) and collecting statistics or informative summaries about that data. The purpose of these statistics may be to: # Find out whether existing data can be easily used for other purposes # Improve the ability to search data by tagging it with keywords, descriptions, or assigning it to a category # Assess data quality, including whether the data conforms to particular standards or patterns # Assess the risk involved in integrating data in new applications, including the challenges of joins # Discover metadata of the source database, including value patterns and distributions, key candidates, foreign-key candidates, and functional dependencies # Assess whether known metadata accurately describes the actual values in the source database # Understanding data challenges early in any data intensive project, so that late project surprises are avoided. Finding dat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer File
A computer file is a computer resource for recording data in a computer storage device, primarily identified by its file name. Just as words can be written to paper, so can data be written to a computer file. Files can be shared with and transferred between computers and mobile devices via removable media, networks, or the Internet. Different types of computer files are designed for different purposes. A file may be designed to store an Image, a written message, a video, a computer program, or any wide variety of other kinds of data. Certain files can store multiple data types at once. By using computer programs, a person can open, read, change, save, and close a computer file. Computer files may be reopened, modified, and copied an arbitrary number of times. Files are typically organized in a file system, which tracks file locations on the disk and enables user access. Etymology The word "file" derives from the Latin ''filum'' ("a thread"). "File" was used in the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Master Data Management
Master data management (MDM) is a technology-enabled discipline in which business and information technology work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets. Drivers for master data management Organisations, or groups of organisations, may establish the need for master data management when they hold more than one copy of data about a business entity. Holding more than one copy of this master data inherently means that there is an inefficiency in maintaining a " single version of the truth" across all copies. Unless people, processes and technology are in place to ensure that the data values are kept aligned across all copies, it is almost inevitable that different versions of information about a business entity will be held. This causes inefficiencies in operational data use, and hinders the ability of organisations to report and analyze. At a basic level, master data m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Analysis
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively. Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. In statistical applications, data analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Analysis Paralysis
Analysis paralysis (or paralysis by analysis) describes an individual or group process where overanalyzing or overthinking a situation can cause forward motion or decision-making to become "paralyzed", meaning that no solution or course of action is decided upon within a natural time frame. A situation may be deemed too complicated and a decision is never made, or made much too late, due to anxiety that a potentially larger problem may arise. A person may desire a perfect solution, but may fear making a decision that could result in error, while on the way to a better solution. Equally, a person may hold that a superior solution is a short step away, and stall in its endless pursuit, with no concept of diminishing returns. On the opposite end of the time spectrum is the phrase extinct by instinct, which is making a fatal decision based on hasty judgment or a gut reaction. Analysis paralysis is when the fear of either making an error or forgoing a superior solution outweighs the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Visualization
Data and information visualization (data viz or info viz) is an interdisciplinary field that deals with the graphic representation of data and information. It is a particularly efficient way of communicating when the data or information is numerous as for example a time series. It is also the study of visual representations of abstract data to reinforce human cognition. The abstract data include both numerical and non-numerical data, such as text and geographic information. It is related to infographics and scientific visualization. One distinction is that it's information visualization when the spatial representation (e.g., the page layout of a graphic design) is chosen, whereas it's scientific visualization when the spatial representation is given. From an academic point of view, this representation can be considered as a mapping between the original data (usually numerical) and graphic elements (for example, lines or points in a chart). The mapping determines how th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Database Normalization
Database normalization or database normalisation (see spelling differences) is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints. It is accomplished by applying some formal rules either by a process of ''synthesis'' (creating a new database design) or ''decomposition'' (improving an existing database design). Objectives A basic objective of the first normal form defined by Codd in 1970 was to permit data to be queried and manipulated using a "universal data sub-language" grounded in first-order logic. An example of such a language is SQL, though it is one that Codd regarded as ser ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Master Data Management
Master data management (MDM) is a technology-enabled discipline in which business and information technology work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official shared master data assets. Drivers for master data management Organisations, or groups of organisations, may establish the need for master data management when they hold more than one copy of data about a business entity. Holding more than one copy of this master data inherently means that there is an inefficiency in maintaining a " single version of the truth" across all copies. Unless people, processes and technology are in place to ensure that the data values are kept aligned across all copies, it is almost inevitable that different versions of information about a business entity will be held. This causes inefficiencies in operational data use, and hinders the ability of organisations to report and analyze. At a basic level, master data m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Governance
Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance. Macro level On the macro level, data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called ''international data governance''. This new field consists of "norms, principles and rules governing various types of data." Micro level Here the focus is on an individual company. Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. The key focus areas of data governance include availability, usability, consistency, data integrity and data security, standard compliance and inc ... [...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 th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the DW for reporting. Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system. ETL-based data warehousing The typical extract, transform, load (ETL)-based data warehouse uses staging, data integration, and access laye ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Governance
Data governance is a term used on both a macro and a micro level. The former is a political concept and forms part of international relations and Internet governance; the latter is a data management concept and forms part of corporate data governance. Macro level On the macro level, data governance refers to the governing of cross-border data flows by countries, and hence is more precisely called ''international data governance''. This new field consists of "norms, principles and rules governing various types of data." Micro level Here the focus is on an individual company. Here data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality exists throughout the complete lifecycle of the data, and data controls are implemented that support business objectives. The key focus areas of data governance include availability, usability, consistency, data integrity and data security, standard compliance and inc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Functional Dependency
In relational database theory, a functional dependency is a constraint between two sets of attributes in a relation from a database. In other words, a functional dependency is a constraint between two attributes in a relation. Given a relation ''R'' and sets of attributes X,Y \subseteq R, ''X'' is said to functionally determine ''Y'' (written ''X'' → ''Y'') if and only if each ''X'' value in ''R'' is associated with precisely one ''Y'' value in ''R''; ''R'' is then said to ''satisfy'' the functional dependency ''X'' → ''Y''. Equivalently, the projection \Pi_R is a function, i.e. ''Y'' is a function of ''X''. In simple words, if the values for the ''X'' attributes are known (say they are ''x''), then the values for the ''Y'' attributes corresponding to ''x'' can be determined by looking them up in ''any'' tuple of ''R'' containing ''x''. Customarily ''X'' is called the ''determinant'' set and ''Y'' the ''dependent'' set. A functional dependency FD: ''X'' → ''Y'' is called '' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
