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Data Administration Management Association
The Data Management Association (DAMA), formerly known as the Data Administration Management Association, is a global not-for-profit organization which aims to advance concepts and practices about information management and data management. It describes itself as vendor-independent, all-volunteer organization, and has a membership consisting of technical and business professionals. Its international branch is called ''DAMA International'' (or ''DAMA-I''), and DAMA also has various continental and national branches around the world. History The Data Management Association International was founded in 1980 in Los Angeles. Other early chapters were:San Francisco, Portland, Seattle, Minneapolis, NewYork, and Washington D.C. Data Management Body of Knowledge DAMA has published the Data Management Body of Knowledge (DMBOK), which contains suggestions on best practices and suggestions of a common vernacular for enterprise data management. The first edition (DAMA-DMBOK) was published ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Not-for-profit Organization
A nonprofit organization (NPO) or non-profit organisation, also known as a non-business entity, not-for-profit organization, or nonprofit institution, is a legal entity organized and operated for a collective, public or social benefit, in contrast with an entity that operates as a business aiming to generate a Profit (accounting), profit for its owners. A nonprofit is subject to the non-distribution constraint: any revenues that exceed expenses must be committed to the organization's purpose, not taken by private parties. An array of organizations are nonprofit, including some political organizations, schools, business associations, churches, social clubs, and consumer cooperatives. Nonprofit entities may seek approval from governments to be Tax exemption, tax-exempt, and some may also qualify to receive tax-deductible contributions, but an entity may incorporate as a nonprofit entity without securing tax-exempt status. Key aspects of nonprofits are accountability, trustworth ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Security
Data security means protecting digital data, such as those in a database, from destructive forces and from the unwanted actions of unauthorized users, such as a cyberattack or a data breach. Technologies Disk encryption Disk encryption refers to encryption technology that encrypts data on a hard disk drive. Disk encryption typically takes form in either software (see disk encryption software) or hardware (see disk encryption hardware). Disk encryption is often referred to as on-the-fly encryption (OTFE) or transparent encryption. Software versus hardware-based mechanisms for protecting data Software-based security solutions encrypt the data to protect it from theft. However, a malicious program or a hacker could corrupt the data to make it unrecoverable, making the system unusable. Hardware-based security solutions prevent read and write access to data, which provides very strong protection against tampering and unauthorized access. Hardware-based security or assiste ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Management
Data management comprises all disciplines related to handling data as a valuable resource. Concept The concept of data management arose in the 1980s as technology moved from sequential processing (first punched cards, then magnetic tape) to random access storage. Since it was now possible to store a discrete fact and quickly access it using random access disk technology, those suggesting that data management was more important than business process management used arguments such as "a customer's home address is stored in 75 (or some other large number) places in our computer systems." However, during this period, random access processing was not competitively fast, so those suggesting "process management" was more important than "data management" used batch processing time as their primary argument. As application software evolved into real-time, interactive usage, it became obvious that both management processes were important. If the data was not well defined, the data wo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains. Data science is related to data mining, machine learning, big data, computational statistics and analytics. Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyse actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science ( empirical, theoretical, computational, and now data-driven) and asserted that "everything about sc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Big Data
Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe Big data is the one associated with large body of information that we could not comprehend when used only in smaller amounts. In it primary definition though, Big data refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: ''volume'', ''variety'', and ''velocity''. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. ... [...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 incl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Modelling
Data modeling in software engineering is the process of creating a data model for an information system by applying certain formal techniques. Overview Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders, as well as potential users of the information system. There are three different types of data models produced while progressing from requirements to the actual database to be used for the information system.Simison, Graeme. C. & Witt, Graham. C. (2005). ''Data Modeling Essentials''. 3rd Edition. Morgan Kaufmann Publishers. The data requirements are initially recorded as a conceptual data model which is essentially a set of technology independent specifications about the data and is used to discuss initial requirements with ... [...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] |
Data Architecture
Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. Overview A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration, for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems. A data architecture, in part, describes the data structures used by a business and its computer applications software. Data architectures address data in storage, data in use, and data in motion; descriptions of data stores, data groups, and data items; and mappings of those data artifacts to data qualities, applications, locations ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Management
Information management (IM) concerns a cycle of organizational activity: the acquisition of information from one or more sources, the custodianship and the distribution of that information to those who need it, and its ultimate disposal through archiving or deletion. This cycle of information organisation involves a variety of stakeholders, including those who are responsible for assuring the quality, accessibility and utility of acquired information; those who are responsible for its safe storage and disposal; and those who need it for decision making. Stakeholders might have rights to originate, change, distribute or delete information according to organisational information management policies. Information management embraces all the generic concepts of management, including the planning, organizing, structuring, processing, controlling, evaluation and reporting of information activities, all of which is needed in order to meet the needs of those with organisational r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
A Guide To The Business Analysis Body Of Knowledge
''A Guide to the Business Analysis Body of Knowledge'' (BABOK) is a guide about business analysis, issued by the International Institute of Business Analysis (''IIBA''), attempting to reflect current best practice and to provide a framework that describes the areas of knowledge, with associated activities and tasks and techniques required, from the International Institute of Business Analysis. According to Capability Maturity Model Integration, organisations interested in process improvement should adopt industry standards from the ''Business Analysis Body of Knowledge'' (and other associated references) to lift their project delivery from the ''ad hoc'' to the ''managed'' level. History The BABOK was first published by the International Institute of Business Analysis (''IIBA'') as a draft document ''version 1.4'', in October 2005, 'Reducing the Trend of Failed Business Transformation Projects'' report at Management Concepts for consultation with the wider business analysis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Project Management Body Of Knowledge
The Project Management Body of Knowledge (PMBOK) is a set of standard terminology and guidelines (a body of knowledge) for project management. The body of knowledge evolves over time and is presented in ''A Guide to the Project Management Body of Knowledge'' (''PMBOK Guide''), a book whose seventh edition was released in 2021. This document results from work overseen by the Project Management Institute (PMI), which offers the CAPM and PMP certifications. Much of the ''PMBOK Guide'' is unique to project management such as critical path method and work breakdown structure (WBS). The ''PMBOK Guide'' also overlaps with general management regarding planning, organising, staffing, executing and controlling the operations of an organisation. Other management disciplines which overlap with the ''PMBOK Guide'' include financial forecasting, organisational behaviour, management science, budgeting and other planning methods. History Earlier versions of the ''PMBOK Guide'' were recogni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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