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Glossary of Data management       Article     History   Tree Map
  Encyclopedia of Keywords > Glossaries > Glossary of Data Management /   Michael Charnine

Keywords and Sections
SQL INJECTION
TREATMENT LEARNING
XML DATABASE
DATA MANAGEMENT
DATA DICTIONARY
DATA MART
DATA MODELING
DATA MODEL
DATA MINING
DATA PROFILING
DATA STRUCTURE
DATA STRUCTURES
DATA WAREHOUSE
DATA WAREHOUSES
DATA WAREHOUSING
DISTRIBUTED DATABASE
ENTERPRISE OBJECTS FRAMEWORK
INFORMATION ARCHITECTURE
LOGICAL SCHEMA
METADATA
OLAP
RELATIONAL MODEL
RECORD LINKAGE
RELATIONAL DATABASE
SEMANTIC WEB
AGGREGATIONS
ANALYSIS SERVICES
ARTICLE
ATOMIC TRANSACTION
ATTRIBUTES
AUTOMATIC DATA PROCESSING
BILL INMON
BUSINESS INTELLIGENCE
BUSINESS PROCESS
CALL LEVEL INTERFACE
CHARLES BACHMAN
CLIVE FINKELSTEIN
COLUMN
COMPUTER FILE SYSTEM
CONCURRENCY CONTROL
COPYRIGHT
CUBES
DATA
Review of Short Phrases and Links

    This Review contains major "Glossary of Data Management"- related terms, short phrases and links grouped together in the form of Encyclopedia article.

Sql Injection

  1. SQL Injection is a hacking technique which attempts to pass SQL commands through a web application for execution against a backend database.
  2. SQL Injection is a method of exploiting databases via the user interface.
  3. SQL Injection is a relatively new technique, and hackers are still exploring the many different possibilities.
  4. SQL Injection is a widespread but little known problem amongst software developers and web masters.
  5. SQL Injection is one of the most common weak spots of web applications. (Web site)

Treatment Learning

  1. The output of a treatment learning session is a treatment, a conjunction of attribute-value pairs.
  2. In data mining and treatment learning, association rule learners are used to discover elements that occur in common within a given data set [1].

Xml Database

  1. But what we ended up doing was going with something suggested in ANOTHER chapter - building an embedded XML database.
  2. The Native XML database can be a "repository" of these efforts with XML Instance documents (i.e. (Web site)
  3. Typically the Native XML database does not subscribe to the concept of one data model to describe the entire database. (Web site)

Data Management

  1. Data Management is a broad field of study, but essentially is the process of managing data as a resource that is valuable to an organization or business. (Web site)
  2. Data Management is a company that provides custom and stock forms and related computer supplies to other businesses. (Web site)
  3. Data Management is a partnership between business areas and information technology staffs.
  4. Data Management is the business of managing a resource.
  5. Data Management is the process of planning, co-ordinating and controlling an organisations data resource.

Data Dictionary

  1. A Data Dictionary is a form of metadata or "data about the data. (Web site)
  2. A data dictionary is a "document" that shows relationships between.
  3. A data dictionary is a model that allows you to look at the properties of all the data in your system in a very analytical and structured fashion. (Web site)
  4. A data dictionary is a set of files that define fields for each record of a Btrieve file.
  5. Data Dictionary is a central source of data in a data management system. (Web site)

Data Mart

  1. A data mart is a collection of subject areas organized for decision support based on the needs of a given department.
  2. A data mart is a collection of subject areas organized for decision support system based on the needs of a given department. (Web site)
  3. A data mart is a departmentalized form of a data warehouse.
  4. A data mart is a repository of data gathered from operational data and other sources that is designed to serve a particular community of knowledge workers.
  5. A data mart is a simpler form of a data warehouse focused on a single subject (or functional area) such as sales, finance, marketing, HR etc.

Data Modeling

  1. Data Modeling is a core skill for data professionals, and is a full time job for a small but growing number of IT practitioners.
  2. Data Modeling: A method used to define and analyze data requirements needed to support the business functions of an enterprise.
  3. Data modeling is a critical skill for IT professionals including: database administrators (DBAs), data modelers, business analysts and software developers.
  4. Data modeling is a first step in designing an object-oriented program. (Web site)
  5. Data modeling is a first step in doing object oriented programming. (Web site)

Data Model

  1. A data model is a collection of concepts used to describe data.
  2. A data model is an abstract model that describes how data is represented and used. (Web site)
  3. A data model is the heart and soul of any application, providing a foundation for efficient data entry and retrieval.
  4. Data Model - The data model is the universal translator and is the foundation of the master data management strategy.
  5. Data Model: A logical map that represents the inherent properties of the data independent of software, hardware or machine performance considerations.

Data Mining

  1. As with OLAP, which could mean almost anything, vendors and industry analysts have adopted the term "data mining" somewhat indiscriminately.
  2. Data Mining is a fairly recent and contemporary topic in computing.
  3. Data Mining is a process of exploring and analyzing large quantities of data to discover useful knowledge (patterns and rules).
  4. Data Mining is for executives involved in strategic and tactical decision making as well as operating managers responsible for cost reduction. (Web site)
  5. Data dredging Used in the technical context of data warehousing and analysis, the term "data mining" is neutral.

Data Profiling

  1. Data Profiling is a process whereby one examines the data available in an existing database and collects statistics and information about that data. (Web site)
  2. Data profiling is a business-critical process that is completed during data migration, data warehouse and quality assessment projects. (Web site)
  3. Data profiling is a critical step in the lifecycle.
  4. Data profiling is a feature that enables you to discover inconsistencies and anomalies in your source data and then correct them.
  5. Data profiling is a fundamental step that should begin every data-driven initiative.

Data Structure

  1. A data structure is an item in memory which perhaps improves the utilization of the memory.
  2. Data structure - The logical and physical way of organizing digital data in a database.
  3. Data structure is the pattern to store data in a computer so that it can be used efficiently.
  4. The data structure is based on the idea to identify shortest path subtrees with the regions in the plane they cover. (Web site)

Data Structures

  1. Data Structures is a Colorado Front Range based company, founded in 1994 by Scott English, a 23-year veteran of the telecommunications industry.
  2. Data structures are implemented using the data types, references and operations on them provided by a programming language.
  3. The data structures are defined in object classes, which also include executable code (methods).

Data Warehouse

  1. A Data Warehouse is a database designed to support decision making in organizations. (Web site)
  2. A Data Warehouse is a physically separate store of data transformed from the application data found in operational environments.
  3. A Data Warehouse is a repository of similar information belonging to a single entity, available for queries and analysis.
  4. A Data Warehouse is the "corporate memory".
  5. A Data warehouse is a repository of integrated information, available for queries and analysis. (Web site)

Data Warehouses

  1. Data Warehouses are a distinct type of computer database that were first developed during the late 1980s and early 1990s. (Web site)
  2. Data Warehouses are organized as databases that can be used for running queries and reporting.
  3. Data warehouses are arranged around the corporate subject areas found in the corporate data model. (Web site)
  4. Data warehouses are built with materialized views. (Web site)
  5. Data warehouses are designed to perform well with aggregate queries running on large amounts of data.

Data Warehousing

  1. Data Warehousing is a method for gathering and controlling data from different sources making the data easily available for querying and analysis. (Web site)
  2. Data Warehousing is a part of the KnowledgeStorm Network. (Web site)
  3. Data Warehousing is the procedure of designing, and maintaining a Data Warehouse system. (Web site)
  4. Data warehousing is a complex subject that requires expertise in order to set it up and use it properly.
  5. Data warehousing is an efficient way to manage and report on data that is from a variety of sources, non uniform and scattered throughout a company.

Distributed Database

  1. A Distributed database is a collection of multiple, logically interrelated databases distributed over a network. (Web site)
  2. A distributed database is a collection of databases which are distributed over different computers of a computer network.
  3. A distributed database is a collection of multiple, logically interrelated databases distributed over a computer network.
  4. A distributed database is a database in which portions of the database are stored on multiple computers within a network.
  5. A distributed database is a network of databases managed by multiple database servers that appears to a user as a single logical database.

Enterprise Objects Framework

  1. On the other hand, interface layer is a part of Enterprise Objects Framework.
  2. NeXT's second attempt came in 1994 with the Enterprise Objects Framework (EOF) version 1. (Web site)
  3. Core Data builds on some of the concepts of enterprise-class database application frameworks, such as the Enterprise Objects Framework in WebObjects.

Information Architecture

  1. Information Architecture is a science of organization.
  2. Information Architecture is a skillset concerned with organizing information so it can be found. (Web site)
  3. Information architecture is a vital component of defining the user experience.
  4. Information architecture is all the components of the enterprise that are required to manage information. (Web site)
  5. Information architecture is the frameworks, processes, projects, policies and procedures to manage and use valuable enterprise information assets. (Web site)

Logical Schema

  1. A Logical Schema is a data model of a specific problem domain that is in terms of a particular data management technology. (Web site)
  2. A logical schema is a named set of these types of relationships and provides a set of rules to control how data is returned from the database.
  3. The logical schema is a casual representation of what goes where and in what form.

Metadata

  1. Metadata are data about data. (Web site)
  2. Metadata are data on data. (Web site)
  3. Metadata are frequently stored in a central location and used to help organizations standardize their data.
  4. Metadata are more properly called an Ontology or Schema when structured into a hierarchical arrangement.
  5. Metadata are of special interest in various fields of computer science, e.

Olap

  1. In its broadest usage the term "OLAP" is used as a synonym of " data warehousing ".
  2. OLAP is a platform upon which decisions are made.
  3. OLAP is a powerful tool that is widely used by the business community to analyze large financial data sets. (Web site)
  4. OLAP is a specific way of financial and statistical data representation for executives, specialists and analysts. (Web site)
  5. OLAP is a technology that can be distributed to many users using a variety of platforms.

Relational Model

  1. The relational model is an implementation of the relational algebra and set theory branches of mathematics to the design and working of databases.
  2. The relational model is based on the mathematics of set theory.
  3. The relational model is the most popular type of database and an extremely powerful tool, not only to store information, but to access it as well. (Web site)
  4. The relational model is the most widely used data model.
  5. The relational model was proposed by E. F. Codd in 1970.

Record Linkage

  1. Record Linkage is a ---hard--- problem.
  2. Record Linkage was among the most prominent themes in the History and computing field in the 1980s, but has since been subject to less attention in research. (Web site)
  3. Record linkage is a fundamental issue occurring in many large applications that involve integrating multiple information sources.
  4. Record linkage is a fundamental problem when integrating multi- pleinformation sources.
  5. Record linkage is a useful tool when performing data mining tasks, where the data originated from different sources or different organizations.

Relational Database

  1. A Relational Database is a set of database tables that are related using keys from other database tables.
  2. A relational database is a collection of data arranged in table s, also known as relation s.
  3. A relational database is a collection of data arranged in tables , also known as relations .
  4. A relational database is a database A database is an information set with a regular structure.
  5. A relational database is a database based on the relational model .

Semantic Web

  1. The Semantic Web is a Web of actionable information—information derived from data through a semantic theory for interpreting the symbols.
  2. The Semantic Web is a common framework that enables data to be shared and reused across applications and between enterprises and organizations.
  3. The Semantic Web is a mesh of information linked up in such a way as to be easily processable by machines, on a global scale. (Web site)
  4. The Semantic Web is a web of data. (Web site)
  5. The semantic web is a complex solution.

Aggregations

  1. Aggregations are built from the fact table by changing the granularity on specific dimensions and aggregating up data along these dimensions. (Web site)
  2. Aggregations are often created as the sum of the individual records.
  3. Aggregations are totals of member values, such as sales by store manager. (Web site)

Analysis Services

  1. Analysis Services is designed to work in both client-server and completely thin client environments.
  2. Analysis Services is used in many comprehensive business analysis deployments.

Article

  1. The article is based on the results of Harvard University's study in the Andrew W. Mellon Foundation grant on electronic journal archiving.
  2. The article was based on his MIT Ph.D. dissertation. (Web site)

Atomic Transaction

  1. An atomic transaction is a database transaction or a hardware transaction which either completely occurs, or completely fails to occur. (Web site)
  2. An atomic transaction is a database transaction which either completely occurs ( commits), or has no effects ( rolled back).
  3. An atomic transaction is a set of one or more operations where either all the operations take effect or none of them take effect.
  4. An atomic transaction is a single, irreducible component of a classic transaction, such as making a purchase.

Attributes

  1. Attributes are associated with it.
  2. Attributes are fields or elements, which may in turn have substructure.
  3. Attributes are specific pieces of information which need to be known or held. (Web site)
  4. Attributes are used to provide additional information about elements.
  5. Attributes are usually attached to columns in a dimension table.

Automatic Data Processing

  1. Automatic Data Processing is a nationwide company. (Web site)
  2. Automatic data processing is a key feature for a successful data management of a continuous monitoring process.

Bill Inmon

  1. Bill Inmon is a leading authority on data management and data warehousing. (Web site)
  2. Bill Inmon is a world renowned expert in data management technologies and is the "father" of the data warehouse concept.

Business Intelligence

  1. Business Intelligence is a broad field of study. (Web site)
  2. Business Intelligence is a part of the KnowledgeStorm Network.
  3. Business Intelligence is a process for increasing the competitive advantage of a business by intelligent use of available data in decision making.
  4. Business Intelligence is a process for professionally gathering, processing and disseminating decision-making information to business leaders.
  5. Business Intelligence is a set of business processes for collecting and analying business information. (Web site)

Business Process

  1. A business process is a collection of related structural activities that produce something of value to the organization, its stake holders or its customers. (Web site)
  2. A business process is usually the result of a business process design or business process reengineering activity.
  3. Business Process - A business process is a recipe for achieving a commercial result.

Call Level Interface

  1. The Call Level Interface is an alternative mechanism for executing SQL statements.

Charles Bachman

  1. The roots of IDMS go back to Dr. Charles Bachman Charles W. Bachman is a prominent computer scientist, particularly in the area of databases.
  2. The Network model, also known as the CODASYL model, was developed by Charles Bachman, who received the ACM Turing Award in 1973.
  3. Turing Paper Additional Links Charles Bachman's Papers Charles William Bachman is a prominent computer scientist particularly in the area of databases.

Clive Finkelstein

  1. Clive Finkelstein is a founding father of Information Engineering and he continues to apply its principles.

Column

  1. Column is a subset of the HIGHGROUP index.
  2. Column is part of a join field.
  3. Column is used in a GROUP BY clause, argument of a COUNT(DISTINCT), or in the select list of a SELECT DISTINCT. See HighNonGroup.

Computer File System

  1. A computer file system is a foundational element of any information management system.
  2. Computer file system is a very important part of any network.

Concurrency Control

  1. Concurrency control is a method used to ensure that transactions are executed in a safe manner and follow the ACID rules.
  2. Concurrency control is a method used to ensure transactions are executed in a safe manner and follows the ACID rules. (Web site)
  3. Concurrency control is a very complex subject and good preparation is advisable.
  4. Concurrency control is a well-studied problem in the fields of distributed operating systems and database management.

Copyright

  1. A copyright is a form of protection provided by federal law (Title 17 U.S.C.--101 et seq.).
  2. Copyright - A guide to website copyright.
  3. Copyright is a complex topic.
  4. Copyright is a need in a capitalist society.
  5. Copyright is the legal basis on which most creators earn their income.

Cubes

  1. Cubes are collections of facts and dimensions.
  2. Cubes are data processing units composed of fact tables and dimensions from the data warehouse.
  3. Cubes are logical representation of multidimensional data.The edge of the cube contains dimension members and the body of the cube contains data values.
  4. Cubes are made up of dimensions.
  5. Cubes are no exceptions.

Data

  1. The data is used for query, analysis, and reporting. (Web site)
  2. The data is used for transaction validation by the data capture environment, decision support systems, and for representation of business rules.
  3. Data is the content of databases or data files.

Related Keywords

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  Originally created: February 19, 2008.
  Links checked: June 19, 2013.
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